With a few clicks, he places a digital implant onto the model. With another click, the software runs an artificial intelligence (AI) algorithm that pulls data from the patient’s medical scans and combines it with information about the standard shoulder replacement hardware to generate new specifications for a patient-matched implant. In 4 to 6 weeks’ time, a vendor will deliver a custom 3D-printed device designed to integrate seamlessly with the patient’s body. The goal, Dr. Sanchez-Sotelo says, is to make sure it’s perfect.

In the operating room, Dr. Sanchez-Sotelo dons a high-tech headset. During surgery, the headset projects holograms of the 3D patient model and the custom implant. With a flick of his fingers, he can adjust the image to present new views. The hologram highlights the precise anatomical landmarks detailing where Dr. Sanchez-Sotelo will position and secure the implant.

“It’s like having Superman vision,” he says. “You can see through the body’s structures and see exactly what you’ll need to do during the surgery. This level of detail allows me to complete the surgery faster than ever, and I can place the implant within millimeters and degrees of complete accuracy.”

Technologies like these — augmented, virtual and mixed realities — are revolutionizing medicine across every field from surgery to medical education. As Mayo Clinic works to transform healthcare, scenes that seem like science fiction are already unfolding at all three campuses.

Joaquin Sanchez-Sotelo, M.D., Ph.D., and Giselle Coelho, M.D., Ph.D.

Transforming Pediatric Care

Giselle Coelho, M.D., Ph.D., a Mayo Clinic STR-X (simulation, telemedicine, robotics and experimental education) fellow and pediatric neurosurgeon, has leveraged this technology to address serious brain and skull malformations in infants and young children. In these cases, precision is paramount.

“Pediatric neurosurgery presents unique challenges,” explains Dr. Coelho. “These cases are relatively uncommon, and you may be faced with severe anatomical malformations. You never want the first time you do a procedure to be on an actual child.”

This is where extended reality tools become invaluable. Dr. Coelho’s team combines advanced imaging and 3D modeling technology to transform patient scans into detailed anatomical models.

These aren’t simple visual representations — they’re sophisticated surgical planning tools that clarify important details like the exact location of arteries, the precise dimensions of skull defects, and the spatial relationships between tumors and critical brain structures.

“We can simulate the full surgery before we ever enter the operating room,” Dr. Coelho explains. “The technology allows us to practice our approach, measure exactly how much bone we’ll need for reconstruction, and coordinate with other specialists like plastic surgeons.”

Even more importantly, she says that using augmented reality (AR) headsets projecting holographic images onto the physical model, they can conduct full simulations of the surgery, including nurses and operating room technicians, to ensure that every person knows exactly what to expect before the patient even enters the room.

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The impact of this approach is clear. Dr. Coelho shares an example of a complicated procedure her team conducted on a child from the Amazon region of Brazil with an encephalocele — a rare birth defect causing brain tissue to protrude through an opening in the skull. The team used AR technology to plan and demonstrate the surgical approach to the team and used a patient-specific hybrid model to plan and practice the surgery in advance.

“Traditional surgical planning might show us the general anatomy, but with these tools, we could determine the exact measurements of the defect and precisely calculate how much bone we needed to close it,” says Dr. Coelho.

For children requiring complex neurosurgery, this reduction in operating time isn’t just about efficiency. It means less time under anesthesia and potentially better outcomes. Experts say that this technology can transform not just the surgical experience, but the entire trajectory of a young patient’s life.

In the case of her patient with encephalocele, Dr. Coelho says that the procedure completely changed the child’s life, allowing her to excel in her studies and finally be able to fully engage in her community. “That’s what this is all about,” Dr. Coelho says. “We’re using technology to transform possibilities for our patients.”

Defining Realities

The term “extended reality” encompasses three emerging technologies: virtual reality, augmented reality and mixed reality.

Illustrations by Jason Schneider

Virtual Reality

Virtual reality (VR) technologies are fully digital simulated environments, typically accessed via an immersive headset and sometimes including haptic feedback gloves to allow for environmental interaction.

Augmented Reality

Augmented reality (AR) refers to cases where digital elements are projected onto the real environment, typically using a screen interface or headset.

Mixed Reality

Mixed reality (MR) combines virtual and real elements, such as in training simulations that project virtual models over real surgical dummies to enhance the learning experience.

Virtual Care in Critical Moments

Neurosurgeon Rabih Tawk, M.D., believes that these technologies can, and should, be applied to every field. “Every surgeon is always learning,” he says. “Every patient is different, with unique needs. These simulations provide a valuable new platform for surgical planning, tailoring the approach for everyone. Why shouldn’t all surgeons plan this way?”

Dr. Tawk uses a system called Immersive Touch, consisting of virtual reality goggles and hand controllers, to plan complex aneurysm surgeries. These tools allow him to create detailed 3D visualizations of the surgery site using patient brain scans, providing clearer insights into the patient’s anatomy than could be gleaned from simply looking at static 2D angiograms. These insights, in turn, allow him to generate a precise treatment plan.

Even outside of the operating room, these tools are changing how clinicians collaborate to provide care. Neurointensivist William D. Freeman, M.D., listed a multitude of ways that virtual reality is used in his field, including the use of virtual reality to enable rapid case review and consultations with remote specialists — critical for time-sensitive stroke care.

“In some places, hospitals are even using minimally invasive robots and remote controls in collaboration with on-site care providers so surgeons can place stents in stroke patients completely remotely,” he says. “These tools provide opportunities for expert care even in locations where a clinician of the right specialty is not available on-site.”

With the advancement of 6G technology, which allows for nearly instantaneous transmission of high volumes of data, Dr. Freeman sees a rapid evolution in remote surgical collaboration. In the future, he imagines that Mayo Clinic experts will participate in “4D surgeries,” with multiple surgeons in more than one location working to care for a patient together in three-dimensional virtual space, across the fourth dimension of time.

Advancements in data transmission technology will also enable “holoportation,” allowing remote specialists to participate virtually in consultations or medical procedures via realistic 3D hologram projections. At Mayo Clinic, this could mean that a specialist in Rochester appears to be standing beside a surgical team member in Arizona or Florida, providing guidance in real time while maintaining the feel of a natural face-to-face interaction.

While this may sound like science fiction, to Dr. Freeman, it’s simply the next step in ensuring that patients get the care they need, whenever and wherever they need it.

A Powerful Pairing

Combined with other advanced technologies, such as AI, extended reality tools are propelling surgery into the next century. “These technologies complement each other perfectly,” explains Dr. Sanchez-Sotelo. “AI helps us see and understand patterns in thousands of surgeries, while extended reality lets us apply those insights with unprecedented precision.”

In practice, this partnership begins long before the first incision. AI algorithms analyze vast databases of surgical outcomes to help design patient-specific implants and suggest optimal surgical approaches based on each patient’s unique anatomy. The technology can identify subtle variations that might affect surgical success.

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In the operating room, AI technology processes and interprets imaging data from multiple sources, generating the real-time visualizations that surgeons use via their AR headsets. AI systems can also track and analyze surgical performance metrics, providing instantaneous feedback during training simulations, and allowing trainees and their teachers to track progress against established benchmarks.

These advances are particularly crucial for remote surgery, where Mayo Clinic is pioneering new approaches. Advanced AI filters act as digital stabilizers for robotic surgical systems, eliminating tiny tremors or delays that could impact precision. “These safety systems are essential,” explains Dr. Freeman. “They ensure that even if there’s a minor connectivity hiccup, the robotic system remains steady and precise.”

The Reality of Implementation

Like any emerging technology, there are practical challenges to consider — some of which can be addressed simply by changing the room’s lighting. “The system requires specific environmental conditions to work optimally,” says Dr. Sanchez-Sotelo. “Very bright operating room lights can make it difficult to see the holograms, and certain colors of surgical gloves can interfere with the system’s tracking capabilities. You need a reliable internet connection, and you have to be ready to adapt if the technology experiences issues.”

Some more traditional surgeons have expressed concerns about overreliance on technology. Dr. Sanchez-Sotelo emphasizes the importance of maintaining clinical judgment alongside technological proficiency. “You still have to have common sense and be ready to adjust if the plan doesn’t work out,” he says. “These tools enhance our capabilities, but they don’t replace the need for surgical expertise and decision-making.”

In addition, the financial barriers to adoption can be significant. For institutions in underserved areas, these costs can be prohibitive. However, Dr. Freeman points to reduced recovery times as a benefit that offsets these costs. “Preoperative planning reduces complications during surgery and shortens hospital stays,” he says. “Shortening a patient’s length of stay in the ICU by even a day saves thousands of dollars. The cost-effectiveness ratio is quite favorable. These tools are investments that pay off in better patient outcomes and lower overall costs.”

Personalizing Care Beyond Physical Boundaries

These technologies represent more than just tools — they’re part of a new frontier in personalized medicine. Through Mayo Clinic Platform, healthcare’s first true platform, solution developers are exploring vast datasets and sophisticated AI models to detect diseases earlier, optimize therapies and generate more accurate diagnoses. When combined with extended reality tools, this creates unprecedented opportunities to tailor care to each patient’s unique needs.

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But perhaps most transformative is how these technologies are breaking down barriers to accessing expert care. Dr. Sanchez-Sotelo has seen this firsthand. “In many parts of the world, patients don’t have access to surgeons with expertise in complex procedures,” he says. “Now, I can virtually step into an operating room anywhere in the world. I can guide another surgeon in real time, showing them exactly where to place instruments, helping them develop new skills. We’re not just treating today’s patient — we’re helping doctors provide better care for all their future patients.”

These technologies demonstrate that distance need not be a barrier to receiving the highest level of care, that expertise can be shared instantly across continents, and that the future of medicine is both highly technical and deeply human.

“If I’m the patient, I want that top specialist for my critical condition available immediately,” says Dr. Freeman. “These technologies make that possible. They allow us to bring Mayo’s expertise directly to patients, wherever they are, whenever they need it. That’s not just innovation — it’s transformation.”

The post Digital Dimensions appeared first on Mayo Clinic Magazine.

AI holds incredible promise for the future of medicine, but it takes more than just algorithms to make that promise a reality.

— Louis V. Gerstner, Jr.

"AI holds incredible promise for the future of medicine, but it takes more than just algorithms to make that promise a reality,” says Louis V. Gerstner, Jr. “It requires a commitment to innovation and to the talented individuals who can turn theory into practice. By creating the Gerstner Scholars Program at Mayo Clinic, we ensure that clinicians with patient-first strategies have what they need to redefine what’s possible in healthcare."

The inaugural cohort of 10 Gerstner Scholars has already demonstrated exceptional promise, presenting high-impact projects poised to significantly advance healthcare. Their innovative proposals highlight the transformative potential of AI in medicine.

Learn more about Gerstner Philanthropies.

FIRST COHORT OF GERSTNER SCHOLARS 

Alina M. Allen, M.D. | Rochester, Minnesota
Division of Gastroenterology and Hepatology

Project: Intelligent and Automated Clinical Care Pathway for Diagnosis and Referral of Patients with Liver Disease and Fibrosis 

Dr. Allen will develop and implement an automated clinical care pathway that integrates machine learning models to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD), also known as fatty liver disease, which affects 1 in 3 adults and is one of the most common causes of liver transplantation. This fully automated care pathway will identify patients at risk of MASLD, stage the severity of liver fibrosis/scarring, and trigger appropriate diagnostic imaging and hepatology referrals.

Carrie M. Carr, M.D. | Rochester, Minnesota
Department of Radiology

Project: GRACIE: Glioma Review Using AI, Clinical Notes, Imaging and Other Electronic Documents

Dr. Carr will use a large language model (LLM) to succinctly abstract data from the electronic health record to present a radiologist with a clear timeline that contains prior radiologic results, radiochemotherapy regimens, surgical procedures and pathology data for patients with primary brain tumors. By having a clear timeline leading up to the current study, radiologists will be better equipped to render higher-quality, more timely interpretation of a patient’s MRI that can be used in clinical care.

Chia-Chun Chiang, M.D. | Rochester, Minnesota
Department of Neurology 

Project: Precision Migraine Treatment: An AI-Powered Approach for Migraine Prevention

Dr. Chiang will construct and implement machine learning models that can accurately predict treatment response to commonly used migraine preventive medications based on clinical phenotypes and electronic health record data elements. Based on promising pilot studies, she will expand variables, validate models and translate models into the clinical practice.

Lauren A. Dalvin, M.D. | Rochester, Minnesota
Department of Ophthalmology 

Project: AI-Assisted Screening for Choroidal Melanoma

Choroidal melanoma is the most common adult intraocular cancer, which is fatal in up to 50% of patients. Dr. Dalvin will leverage Mayo Clinic’s robust database within the ocular oncology service to develop machine learning models that detect and triage high- and low-risk choroidal lesions to improve patient survival rates by early cancer detection.

Christopher A. Dinh, M.D. | Rochester, Minnesota
Division of Hospital Internal Medicine

Project: Implementing Predictive AI Models to Improve Hospital Patient Flow

Dr. Dinh will implement three predictive AI models into the clinical practice to improve hospital patient flow and discharge efficiency. Early identification of hospitalized patients with complex discharge needs can help focus case management resources earlier on in the hospital stay and thereby reduce hospital length of stay. An efficient hospital discharge will also improve the experience for patients and their families.

Antonio J. Forte, M.D., Ph.D. | Jacksonville, Florida
Department of Surgery

Project: Development of a RAG-LLM in Virtual Assistant for Post-Operative Surgical Care

Dr. Forte will enhance an AI virtual assistant with a retrieval augmented generation (RAG)-based LLM to provide more accurate, personalized and adaptable postoperative care support to patients and improve patient outcomes and safety.

William D. Freeman, M.D. | Jacksonville, Florida
Department of Neurosurgery 

Project: SAHVAI: Subarachnoid Hemorrhage Volumetric Artificial Intelligence

SAHVAI is an AI tool for measuring the amount of blood leaked into the spaces and folds of the brain in patients with life-threatening aneurysmal bleeding, reducing time to intervention and improving risk stratification for serious events. “Time is brain,” and SAHVAI has demonstrated significant promise in initial studies for acute stroke care. Dr. Freeman will advance this tool and enhance SAHVAI readiness for wider implementation.

Scott A. Helgeson, M.D. | Jacksonville, Florida
Division of Allergy and Pulmonary Medicine 

Project: AI Based Non-Invasive Detection of Blood Pressure Using Photoplethysmogram (PPG)

Dr. Helgeson will develop a cuffless, non-invasive AI model to accurately predict blood pressure across all ranges — from hypotension to hypertension — using PPG signals, trained with arterial line blood pressure measurements for enhanced precision and comfort in patient care.

Abhinav Khanna, M.D. | Rochester, Minnesota
Department of Urology

Project: Leveraging Artificial Intelligence to Personalize Early Detection and Monitoring of Kidney Cancer

A large percentage of patients with kidney cancer present with advanced stages of disease, including a subset of patients with incurable metastatic kidney cancer. Early detection is paramount to facilitate early intervention and to alter disease trajectory. Dr. Khanna will apply a novel AI algorithm to facilitate early detection of kidney tumors and personalize tumor surveillance strategies based on deep learning analysis of tumor radiomic features.

Irbaz B. Riaz, M.B.B.S., Ph.D. | Phoenix, Arizona
Division of Hematology and Oncology 

Project: Precise and Intelligent Outreach for Therapeutics and Clinical Trial Yield (PRIORITY)

Using AI, Dr. Riaz will implement an LLM-enabled chatbot to proactively inform patients of relevant new Food and Drug Administration-approved clinical trials and treatments, improving access and engagement beyond clinical visits and increasing accrual to clinical trials through targeted outreach.

The post Gerstner Scholars Program in AI Translation appeared first on Mayo Clinic Magazine.

Seeing the Unseen

Pancreatic cancer remains one of the deadliest forms of the disease, with the American Cancer Society reporting a five-year survival rate of 13% in its 2024 statistics. It’s one of the lowest survival rates of any cancer, due in large part to the challenge of identifying pancreatic cancer early. But Mayo Clinic clinician-investigators have always believed it was possible to identify pancreatic cancer at a stage before symptoms become present — significantly boosting the odds of survival.

Time after time, early screening risk programs failed to make meaningful inroads. Individual review of patient imaging files is challenging — the human eye isn’t proficient at making the diagnosis that early, causing false-positive rates to soar.

But Mayo Clinic had a differentiator. It was a deep, longitudinal dataset dating back decades that included people who had been diagnosed with late-stage pancreatic cancer. The depth of the data meant that researchers could look back even earlier in patient records to review imaging taken 12 months or more prior to the discovery of cancer.

“The data allowed our teams to train an artificial intelligence (AI) model on that patient cohort that could pick up those early-stage pancreatic cancer cases with really high sensitivity and specificity,” says Matthew Callstrom, M.D., Ph.D., who serves as medical director of the Strategy Department and medical director of Mayo Clinic’s Generative Artificial Intelligence Program. “It could do this at a very high accuracy — 97%.”

Our aspirations for AI are to impact patient outcomes.

— MATTHEW CALLSTROM, M.D., PH.D.

Dr. Callstrom says the work of Ajit Goenka, M.D.; Panos Korfiatis, Ph.D.; and Eric Williamson, M.D., and their teams showed that Mayo Clinic could determine whether a person had pancreatic cancer through applied AI at an early point in disease progression. Currently in the U.S., lung cancer causes the most cancer deaths, followed by colorectal cancer and then pancreatic cancer.

“We think we can shift the needle on that,” Dr. Callstrom says.

While discovery in medicine is challenging, translating those discoveries into clinical practice can be even more complex, according to Dr. Callstrom. This year, Mayo Clinic research scientists including Aadel Chadhuri, M.D., Ph.D.; Suresh Chari, M.D. (emeritus); Dr. Goenka; and Mark Truty, M.D., M.S., are testing the pancreatic cancer algorithm in the AI-PACED clinical trial, an area where Mayo Clinic excels. By focusing on patients at high risk for pancreatic cancer, particularly those with a family history of the disease, Mayo Clinic can evaluate new AI-driven approaches with more impact.

Mayo Clinic embeds scientists directly in clinical practice where they work alongside clinicians who understand the problems patients face and have access to the data. Together, they develop and test AI solutions in real time.

“That’s across the entire organization, and there are incredible discoveries being made all over,” he says.

FROM THERE TO HERE

Like many clinicians at Mayo Clinic, Dr. Callstrom’s background is varied and unique. He was a chemical engineering major at the University of Minnesota who stayed to do a Ph.D. in chemistry, followed by a postdoctoral opportunity at Harvard University.

From there, he began teaching chemistry at The Ohio State University. When one of his friends who was also a colleague at Ohio State was diagnosed with colon cancer, the experience deeply affected him.

“I became very motivated to try to impact patients’ lives. I went into medical school and was very fortunate to get into Mayo Medical School (now called Mayo Clinic Alix School of Medicine),” Dr. Callstrom says. “I’ve done all my training here, and my clinical emphasis is on treating patients with cancer.

“So, I do interventional oncology treating patients and trying to help them through a very difficult period in their life. And through the other aspects of my work in AI, we are hopefully developing cures for them.”

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In fact, Mayo Clinic has been looking at AI approaches for more than a decade, and its emergence in imaging over the most recent years dovetailed with Dr. Callstrom’s interests in figuring out how he could help the lives of as many patients as possible.

“He’s a pioneer in AI, working on machine learning back when most people weren’t thinking about that,” says Jim Rogers, CEO, Mayo Clinic Digital Pathology. “His singular focus has always been: ‘What can I do to improve care for folks?’

“There’s real courage and vision there. Because of him and others throughout the institution, Mayo now has more machine learning AI algorithms in actual practice — not just theory — than any other organization.”

ALREADY ACTIVE

Results from that early work are popping up all over Mayo Clinic, which has more than 60 AI models already deployed behind the scenes every day. This means that the solutions have been built and validated and are running automatically.

One area ripe for innovation is in cardiovascular medicine. Itzhak Zachi Attia, Ph.D.; Paul Friedman, M.D.; Francisco Lopez-Jimenez, M.D., M.S.; and Peter Noseworthy, M.D., M.B.A., among a team of many others, are using EKG data to train various models to look for issues. Already one algorithm has been found to be effective in accurately identifying atrial fibrillation (AFib) at an early stage. Using a similar approach to the clinical trial in pancreatic cancer, the team discovered that AFib could be detected more than six months before it becomes clinically important.

“The reason that’s impactful is that once atrial fibrillation starts, clots can form in the heart, and those clots can travel to the brain and cause a stroke,” Dr. Callstrom says. “So, if you can stop that or prevent it from happening, you avoid a debilitating outcome for a patient and get them on medication early.”

Another model can diagnose patients with low ejection fraction, a form of heart failure, before symptoms are present, allowing doctors to intervene before the issue becomes critical.

“That model runs on every Mayo patient who has an EKG now,” Dr. Callstrom says. “Our cardiovascular medicine team ran a clinical trial in our health system with 20,000 patients to find out that this did have an impact on patient outcomes. We were able to measure it, and it picked up many patients with unsuspected heart failure or AFib. It was pretty amazing.”

EXPANDING THE FOUNDATION

Jim Rogers, who also serves as the senior administrator for the Generative AI Program, emphasizes that Mayo Clinic’s AI approaches align with the organization’s Bold. Forward. strategy to enhance internal care delivery while pursuing broader healthcare transformation.

The work is purposefully iterative. While each project is initially focused on a specific application or disease, Mayo’s established structure allows new learnings to be expanded to other areas by encompassing disciplines like genomics, pathology, imaging, text analysis, voice recognition and more.

The goal? Practical integration of all these elements to benefit physicians’ abilities to solve the needs of patients.

“We’re learning from every activity and with each step forward,” Jim says. “We’re not doing this out of mere curiosity — we want practical impact as quickly as possible. When a patient walks into one of our rooms, they expect us to have all the information needed to effectively treat them.”

CONNECTED CLINICIANS

AI’s impact isn’t just limited to disease identification and treatment. It’s helping physicians connect on a deeper level with patients too.

Mayo Clinic is using AI-powered ambient listening technology to transform patient encounters. Instead of clinicians typing notes during conversations — which can detract from personal interaction — the AI system captures and summarizes the discussion automatically. Then, the clinician can rapidly review and approve the notes, ensuring accuracy in the patient’s record.

We’re not doing this out of mere curiosity — we want practical impact as quickly as possible.

— JIM ROGERS, CEO, MAYO CLINIC DIGITAL PATHOLOGY

Dr. Callstrom says this innovation eliminates a difficult choice many physicians face: either document during the visit or spend extra time recording notes later in the day, hours after the appointment. With ambient AI handling documentation in the background, providers can focus entirely on patient interaction, ultimately bringing more humanity into healthcare.

A PROMISE-FILLED FUTURE

Even with all the advances, it’s what’s on the horizon that excites Dr. Callstrom the most.

Mayo Clinic is leveraging AI to analyze complex data in unprecedented ways — from genomics and digital pathology to cellular-level imaging. It’s all part of the organization’s mission in this new era to ensure the needs of the patient come first.

“Our aspirations for AI are to profoundly impact patient outcomes,” Dr. Callstrom says. “One of the things we always talk about is trying to identify disease at a state where we can intervene early. Previously, it’s been hypothetical — ‘If we had the right data, we could do this.’ It turns out with AI we can.”

The post Seeing the Unseen appeared first on Mayo Clinic Magazine.

Whether excelling as an elite athlete or dealing with an unexpected medical condition, she has met each new chapter head-on.

Her determination extends to every aspect of her life, including her tireless work for Mayo Clinic Platform. In this role, she is part of a team tackling the transformation of healthcare to benefit patients around the world.

A Natural-Born Athlete

Dr. Turkowski grew up in Richmond, Minnesota, with two athletic brothers and a dad who was a coach, so sports were a natural fit.

She wanted to play hockey in high school even though there were no female players on the team. Undaunted, she became the first. She continued to excel in multiple sports and received an athletic scholarship to St. Cloud State University for volleyball.

Despite being an experienced athlete, in 2008 Dr. Turkowski suddenly began having trouble completing routine workouts. She sought help from several doctors.

No one had answers.

“One day I was walking on a treadmill, and I didn’t feel right,” Dr. Turkowski remembers. “It was like having tunnel vision. My ears were buzzing. My heart went nuts, and I had to get help.”

The next thing Dr. Turkowski remembers is waking up in an ambulance. Her care team ran tests at the hospital, but she went home without answers. She spent the next several weeks worrying and waiting before deciding to go to Mayo Clinic.

From Elite Athlete to Heart Failure

At Mayo Clinic, Dr. Turkowski was diagnosed with stage 2 heart failure and ventricular tachycardia, a type of irregular heartbeat caused by scarring on her heart. She would later learn this was likely a result of myocarditis — inflammation of the heart muscle, usually triggered by a viral infection.

As a seasoned team athlete, Dr. Turkowski immediately recognized how teamwork drove her care at Mayo Clinic.

“My care team told me, ‘Let’s do this together. It might be a long journey, but we’re not going to give up on you,’” she recalls. “The experience was in line with everything that I knew would create success. They brought me in as part of the team. That’s huge.”

Determined to have the highest quality of life possible, Dr. Turkowski began treatment with medications and procedures to disrupt the tissue causing the arrythmia. Then life threw her another curve ball. During her second procedure, Dr. Turkowski went into cardiac arrest on the table.

“I didn’t have a pulse,” Dr. Turkowski says. “They had to give me CPR to get my heart started again. After that, my doctor told me it was time to live a recreational life instead of being a competitive athlete. It was time to find something else to fill my cup.”

Charting a New Course

Dr. Turkowski’s diagnosis forced her to rethink the way she pushes herself physically. But it also motivated her to reevaluate her professional goals, and she credits her patient experience at Mayo Clinic and the organization’s unique approach to collaboration as the inspiration.

Dr. Turkowski left her job as an accountant to pursue her doctorate from Mayo Clinic Graduate School of Biomedical Sciences. After graduation, she spent five years at Mayo Clinic researching genetic heart conditions. During her time in Cardiovascular Medicine, she used artificial intelligence (AI) models to study how data can provide insights into medical conditions.

Then, Dr. Turkowski had an opportunity in 2020 to meet John D. Halamka, M.D., M.S., the Dwight and Dian Diercks President, Mayo Clinic Platform, and Michael D. Brennan, M.D., President's Strategic Initiative Professor.

“I knew with my business skills in the accounting world and my science background as a researcher this would be the perfect fit,” she recalls. “I knew I could make a difference here.”

Dr. Turkowski joined Mayo Clinic Platform as a postdoctoral researcher, becoming one of the first eight members. Today, the team has grown to more than 150 with Dr. Turkowski serving as director of Services and Solutions Development.

“I have a personal calling to Mayo Clinic Platform,” says Dr. Turkowski. “My role is to translate solutions so patients can start down a better path sooner. We have to start before the problem happens. That’s how we are going to change healthcare.”

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Building the Ecosystem

Dr. Turkowski describes Mayo Clinic Platform as an ecosystem, noting that it is not about Mayo Clinic alone but the entire world. It’s a community of data, collective challenges and scalable solutions.

Mayo Clinic Platform teams carefully research and review provider markets, listening to the challenges of physicians and other healthcare providers. Once these needs are identified, Dr. Turkowski and her colleagues turn to the data to determine how AI can be used to optimize clinical workflow and improve patient care.

“The data is what makes Mayo Clinic Platform so powerful,” says Dr. Turkowski. “We are developing our data network with partners from all over the world. And when organizations join, they are bringing their data to this ecosystem. It is the foundation to finding solutions for patients.”

As of November 2024, Mayo Clinic Platform’s distributed data network includes de-identified information from more than 38 million patients from healthcare organizations spanning four continents. These member organizations maintain control of their data, and innovators query it using a privacy-protected process. All data must be structured consistently and stripped of any identifiable information.

For example, one of the projects Dr. Turkowski is currently working on is a practice transformation effort with Mayo Clinic’s gastroenterology team. Videos of endoscopies, minimally invasive procedures to examine the digestive system, are valuable to this group, yet the capability to include videos within the Platform’s dataset does not currently exist. Dr. Turkowski and her team are collaborating with the gastroenterology team to develop a way to make this possible.

“I love being connected to the clinical practice on a daily basis,” she says. “I get to work with amazing innovators at Mayo Clinic and witness their passion for healthcare. Their love for caring for their patients is amazing.”

In the Right Place

Dr. Turkowski says she’s grateful to be part of a team that shares her determination to succeed.

“When I was a patient, I saw how Mayo approached care,” says Dr. Turkowski. “True success comes from a solid, dedicated team. I saw it in my research, in my education and in Mayo Clinic Platform. We work together as a team. We are driven. We have a mission, and we have the grit and commitment to transform healthcare in a way that was previously unimaginable.”

Today, years after she lost consciousness on a treadmill, Dr. Turkowski is moving forward at full speed toward a better future in healthcare. “I’m fortunate to be part of this team. And I’m fortunate to be alive. There were times I didn’t know if I was going to wake up,” she says. “I’m sitting here today because Mayo saved my life, and I get to work on something really special. I’m in the right place.”

The post From Heart Challenge to Healthcare Innovation appeared first on Mayo Clinic Magazine.

Physicians and researchers across Mayo Clinic are developing and using AI-driven tools that accelerate new knowledge, solutions and technologies. Mayo Clinic is also partnering with other leading institutions worldwide to better leverage resources and advance responsible, effective and trustworthy AI practices.

Discover how AI is making an impact on patient care at Mayo Clinic.

Revealing Seizure Hot Spots to Accelerate Life-Changing Care

Drug-resistant epilepsy often requires surgery to remove seizure-causing brain tissue.

First, though, patients must typically undergo a different surgery to implant electrodes in their brain, followed by weeks of monitoring neural activity to identify where the seizures are located.

It’s challenging for physicians to accurately detect high-frequency brain waves because of their short duration and low amplitude, as well as environmental noise. Physicians currently use a labor-intensive manual data analysis process to remove unwanted or corrupted data points.

Mayo Clinic researchers have developed new AI tools to more rapidly and accurately pinpoint seizure hot spots in patients with drug-resistant epilepsy. Nuri Ince, Ph.D., a consultant in the Mayo Clinic Department of Neurologic Surgery, is the senior author of the study, which was published in the journal Nature Communications Medicine.

Enhancing the identification process means patients can more quickly undergo targeted tissue removal surgery, which is critical for achieving seizure freedom. Faster identification also reduces the need for prolonged monitoring after electrode implantation, minimizing risks like infection — which is five times more likely to occur in children than in adults during prolonged stays in epilepsy monitoring units.

The group's future work will focus on transforming the framework into a fully digital, real-time system that can interpret the brain waves during electrode implantation surgery and provide feedback to the clinical team regarding the location of the epileptic brain tissue.

To learn more, visit Mayo Clinic News Network.

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Mayo Clinic Digital Pathology Opens New Frontiers in Medicine

In early 2025, Mayo Clinic launched Mayo Clinic Digital Pathology, a platform that will accelerate diagnostic speed and accuracy, leading to faster, more personalized treatments and cures.

This new platform involves collaborations with NVIDIA, a world leader in accelerated computing, and Aignostics, an industry leader in building AI models for digital solutions.

Mayo Clinic Digital Pathology takes advantage of unique Mayo Clinic assets:

• Mayo Clinic Platform, which unites data resources, solution developers and novel deployment methods to drive digital innovation.
• Mayo Clinic Laboratories, a global leader in diagnostics that provides advanced testing and pathology services for healthcare organizations worldwide.

Mayo Clinic Digital Pathology uses large, diverse datasets to build powerful artificial intelligence models in pathology, which addresses a major challenge in the field: the widespread use of analog processes. This hinders access to critical diagnostic data that could be used to expand diagnostics and treatments and speed the development of new therapies to benefit patients.

The early results of this collaborative, multidisciplinary effort are promising. As of mid-January 2025, Mayo Clinic Digital Pathology has leveraged 20 million digital slide images linked to 10 million patient records that incorporate treatments, medications, imaging, clinical notes, genomic data and more.

To learn more, visit Mayo Clinic News Network.

Providing Clinicians With the Most Useful Medication Alerts

Two Mayo Clinic Ph.D. candidates, Caroline Grant and Jean Marrero-Polanco, are exploring how AI can provide clinicians with predictive alerts about their patients’ potential response to specific medications in a study published in the journal Clinical and Translational Science.

Grant and Marrero-Polanco, under the mentorship of senior study author Arjun Athreya, Ph.D., a computer scientist in the Mayo Clinic Department of Molecular Pharmacology and Experimental Therapeutics, surveyed 305 clinicians across Mayo Clinic sites in Arizona, Florida and Minnesota, as well as Mayo Clinic Health System, about their communication preferences.

The researchers used AI to process large volumes of survey data and uncover insights that are hard to detect with traditional methods. They found that clinicians generally prefer concise, individualized alerts that use patient-specific genomic data to help personalize their care, rather than more generic or detailed alerts. Concise, individualized alerts are more actionable and less intrusive for clinicians.

The next phase of this research will involve testing these refined alerts in actual clinical settings to determine their effect on clinician burnout and patient outcomes.

To learn more, visit Mayo Clinic News Network.

The post 3 Ways AI Is Improving the Patient Experience at Mayo Clinic appeared first on Mayo Clinic Magazine.

It’s a vision that is close to the couple’s heart, as both have witnessed friends and family pass away from the disease.

“I’ve seen the time, the energy and the emotions that the entire family goes through watching their loved one undergo cancer treatment for months or even years,” says Becky, whose father passed away from melanoma when she was 13 years old. “If we catch the cancer earlier when the treatment isn’t so challenging, it would be life-changing for so many families.”

To help fuel this critical work, Bahman and Becky established the Hoveida Family Foundation Cancer Discovery and Interception Fund through a generous gift from the Hoveida Family Foundation. Becky and Bahman are recognized as Philanthropic Partners.

The fund is helping accelerate Mayo Clinic’s bold vision to revolutionize cancer care. Researchers are using innovative, artificial intelligence (AI)-enabled science to detect cancer earlier, intercept and reverse cancer growth, and intervene before cancer progresses to more advanced disease.

The concept of using AI to find solutions to challenges is a process that Bahman understands well. An engineer and businessman, he co-founded a software company, Open Systems International, in Minnesota in 1992. As the company grew, Bahman and Becky never wavered from their commitment to environmental stewardship, ethical sourcing and treating their employees like members of their own family. After selling the company in 2020, the couple formed their family foundation so that they could “keep doing good.”

The Hoveida Family Foundation is focused on the pursuit of science to help humanity and the environment. This includes critical medical research, and Bahman says that Mayo Clinic was at the top of their list. Bahman, who was born in Iran, recalls hearing of the medical organization as a child.

“I knew that the royal family was seen at Mayo Clinic and that it was the great center of medical care in the world, but I didn’t really know much else at the time,” Bahman says.

That all changed in 1999, when Bahman’s father was diagnosed with colon cancer and selected Mayo Clinic for his care.

“The care he got was excellent,” says Bahman. “I was very impressed with the systems in place, and that’s when I realized what a high-quality institution Mayo Clinic was. Healthcare is moving to a high-tech, data-driven industry, and Mayo is pioneering this work.”

Both Bahman and Becky are patients in the Mayo Clinic Executive Health Program, trusting Mayo Clinic with their personal care as they stay connected with the promising research efforts that they’ve helped make possible — including AI-powered breast cancer detection and early pancreatic cancer detection.

Within breast cancer research, a Mayo Clinic researcher and a researcher from the Karolinska Institute in Sweden have used funds to develop and test a model that better identifies women who are at high risk and would benefit from preventive measures like lifestyle changes and risk-reducing medications. Next steps will be to validate the model. 

In pancreatic cancer research, a physician researcher and his team have designed an AI Pancreas Cancer Early Detection trial, which is expected to launch later this year. The trial will leverage an AI language model to screen 10,000 patients, identifying those at elevated risk for pancreatic cancer.

“The work in pancreatic and breast cancer is so meaningful to us,” explains Becky. “Just before we gave our gift, we had lost a valued employee and friend to pancreatic cancer. The time from diagnosis to death was so short. I had also recently lost a family member to breast cancer. The idea of using science to diagnose these cancers at an earlier stage is incredibly important.”

The Hoveida Family Foundation Cancer Discovery and Interception Fund is also supporting AI-Powered Science and Discovery Awards in Cancer. This program finds and funds the most innovative concepts and proposals from individuals and teams across Mayo Clinic.

“Mayo Clinic has created a great team of researchers, data scientists and AI experts,” says Bahman. “They have a level of passion that I have not seen anywhere else. If a practical solution comes out of this research to detect cancer even six months ahead of when cancer symptoms manifest, that’s a huge advancement in saving thousands of lives. I have great hopes that Mayo Clinic will be successful.”

Becky agrees, adding that she feels pride in being part of Mayo Clinic’s mission to help people everywhere.

“When Mayo Clinic finds solutions, their goal is to disseminate information across the medical field worldwide and make it available to everyone,” says Becky. “They are helping more than their own patients — they are helping the world."

The post Engineering Earlier Cancer Detection Through AI appeared first on Mayo Clinic Magazine.

Making Cancer Care at Home More Available

Cancer Care Beyond Walls has made life a lot easier for patients with cancer and their families.

However, insurance companies do not typically reimburse for at-home chemotherapy infusion, which means that Mayo Clinic is currently underwriting Cancer Care Beyond Walls’ costs.

Mayo Clinic actively engages in federal advocacy work and payer discussions, explains Rosanna Fahy, Platform’s associate vice president for Cancer Care Beyond Walls.

“Sending a nurse to individual patients’ homes is more expensive than having a nurse in a chemo unit who could treat three or four patients at a time,” Fahy says. “I’m grateful for the institutional funding that has supported the program while the data is gathered to meet the reimbursement challenges.”

Rosanna says it’s not surprising that chemotherapy at patients’ homes, when viewed in isolation, is less cost-efficient than at a single clinical location. It simply costs more to have so many moving pieces — nurses, cars, couriers, chemotherapy solutions — than it is to centralize all operations in a single chemo unit.

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But Mayo Clinic is gathering the data to show a fuller financial picture, which may influence future insurance decisions for at-home chemotherapy. Rosanna says that reimbursement models are not just about the cost of care today — they’re about the cost of each patient’s care over the course of their cancer journey, and how the nature of that care influences outcomes.

“We can predict how many times a patient with cancer is likely to have an emergency department visit for some kind of acute care need,” Rosanna explains. “That's knowable and predictable.

“So, if we can intervene early by managing your care at home and avoid that ED visit, that's where the savings start to come — acute care and emergency episodes are higher cost. Savings are not only about direct costs; they’re also in patients’ time and their comfort at home.” 

Collecting data to demonstrate the economic benefits of at-home chemotherapy is just one way Mayo Clinic is working to grow the concept. Other efforts are making a more immediate impact on patients with cancer during their treatment journey.

In 2025, Cancer Care Beyond Walls began in North Dakota, when Altru Health System became the first partner in the Mayo Clinic Care Network to launch the program. Rosanna worked in 2024 to make this expansion possible, alongside Jeremy Jones, M.D., a consultant in the Division of Hematology and Oncology and the medical director of Cancer Care Beyond Walls for Mayo Clinic Platform. Rosanna and Dr. Jones worked closely with Altru, using Platform resources to develop a pragmatic clinical trial.

They both note that there’s a certain symmetry to this. Altru was the first partner to ever join the Mayo Clinic Care Network, Mayo’s community-based rural healthcare delivery system, and now it’s the first organization in the Care Network to join Mayo Clinic in transforming how cancer care is delivered to patients.

“The Platform model is really an enablement model,” Dr. Jones says. “It's less about, ‘Mayo Clinic has to own every single step of the way,’ and more of, ‘Let's show the world how to do things the Mayo Clinic way.’ The beautiful thing about Platform is that we can reach so many more people.”

The post Making Cancer Care at Home More Available appeared first on Mayo Clinic Magazine.

Oliver is remembered for his infectious smile and the love and resilience he radiated to all who knew him, even from the intensive care unit. Born with a rare and incurable genetic epilepsy disorder, he inspired a pioneering program designed to expedite genomic-related diagnoses and enhance definitive patient care. 

"Oliver's life was a brief gift, but he left a mark deeper than his time with us," says his mother, Justine Bates, sitting in the comforting glow of purple lights in honor of her baby boy. Those lights, adorning the windows and a memory tree in her Minnesota home, symbolize epilepsy awareness. Close to her heart, Justine has a tattoo of Oliver's small handprint. 

Oliver's father, Casey Bates, will always remember the quiet evenings spent holding his son after work. He proudly displays his own tattoo that reads "Seize the day," a subtle nod to his son's seizure condition and a reminder to cherish every day. 

"He loved to laugh, and he had the best facial expressions. He was my snuggle bug," Casey says. 

Oliver’s Diagnostic Journey 

Oliver's health journey began when he was just 5 weeks old, when his first seizure led his parents to rush him to a local emergency room. 

The complexity of his case and the initial hospital's difficulty in diagnosing him led them to transfer Oliver to Mayo Clinic for specialized care. At Mayo, Oliver underwent a comprehensive series of tests, including exome sequencing, which specifically examines 20,000 protein-coding genes where many diseases originate. Although this sequencing technique can provide crucial insights into rare conditions, it can require time for detailed analysis and interpretation of the results. 

While Oliver's initial tests did not reveal the cause of his ongoing seizures, the exome sequencing — which took nearly a month to process — finally helped his care team diagnose Oliver's condition: a rare form of epilepsy known as WWOX-related epileptic encephalopathy (WOREE syndrome). Although the diagnosis helped his care team guide Oliver's care, the condition currently has no cure. He passed away on March 10, 2022, surrounded by his loved ones.

A New Era in Genomics 

Rare diseases affect 300 million people worldwide, yet only about 25% of patients ever receive a diagnosis, and often that diagnosis has no available treatments. 

Recent advancements in genomic technologies are beginning to offer a glimmer of hope. Clinicians are using these cutting-edge tools, which leverage artificial intelligence (AI) to scour volumes of data, transform diagnostics, and make it possible to identify and understand rare diseases more quickly and accurately than ever before. This is opening avenues for the development of more treatments. 

Inspiring Genomic Advances 

Witnessing firsthand the critical need for such advancements, Whitney Thompson, M.D., a key member of Oliver's care team, felt compelled to act, moved by Oliver's family's wait for a diagnosis. With support from the Department of Pediatric and Adolescent Medicine and the Center for Individualized Medicine, she launched an ultra-rapid whole genome sequencing program in Mayo Clinic's neonatal intensive care unit (NICU). 

In this pioneering program, which is a collaboration with Rady Children's Institute for Genomic Medicine in San Diego, California, clinicians use new sophisticated technology and AI to sequence a patient's 3 billion DNA base pairs in approximately 48 hours. This comprehensive analysis can identify even the most subtle genetic variants, though it may not always lead to a diagnosis. 

"Rapid diagnoses can lead to lifesaving treatments in some cases, and while not every rare disease has a treatment, every diagnosis brings crucial information that can guide medical decisions and help families anticipate what’s next," says Dr. Thompson, who is completing her fellowship training in neonatal medicine, clinical genomics and bioethics as part of the Clinician Investigator Training Program at Mayo Clinic. 

Oliver's life was a brief gift, but he left a mark deeper than his time with us.

— Justine Bates

Under this program, through the Mayo Clinic Department of Clinical Genomics with Brendan Lanpher, M.D., as practice chair, infants and children admitted to Mayo Clinic's Eugenio Litta Children's Hospital in Minnesota undergo ultra-rapid whole genome sequencing if they meet specific criteria. 

The program, launched at Mayo Clinic in June 2022, has since been expanded to some adults who exhibit symptoms suggestive of genetic disease, enabling them to receive the same rapid, comprehensive DNA analysis. To date, more than 300 infants, children and adults have been offered whole genome sequencing. 

Dr. Lanpher hopes the program will open the door to more patients having access to comprehensive genetic testing. 

"This is the future of medicine," Dr. Lanpher says. "I believe there are many patients with unrecognized or undiagnosed genetic diseases, and by finding and testing these patients early in the course of symptoms, we'll have the best chance at making a difference, finding a treatment and avoiding a diagnostic odyssey." 

Introducing BabyFORce 

Achieving a precision diagnosis is just the first step of a broader goal. Dr. Thompson and her team also have their sights set on rapid individualized therapeutics. She is collaborating with Laura Lambert, Ph.D., director of the Mayo Clinic Functional Omics Resource (FORce), along with Eric Klee, Ph.D., the Everett J. and Jane M. Hauck Midwest Associate Director of Research and Innovation at the Center for Individualized Medicine, and Filippo Pinto e Vairo, M.D., Ph.D., director of the center's Program for Rare and Undiagnosed Diseases. 

Together, they have initiated a first-of-its-kind program called BabyFORce, which uses AI to help clinicians identify individualized therapeutics for some of the smallest and sickest patients with genetic diseases in the Neonatal Intensive Care Unit. 

"We’re tapping into an advanced AI platform that leverages a 'logic programming' approach, applying set rules to combine and analyze various biomedical data sources," says Dr. Lambert. "This could enable researchers to identify potential drug repurposing opportunities, generate hypotheses and uncover novel insights into disease mechanisms." 

She says the approach could also reduce the time and cost associated with developing new therapies and provide hope for patients with limited treatment options. 

Oliver's Impact

Oliver's impact extends beyond medical advancements. As his care unfolded during the challenging times of COVID-19, he also inspired Mayo's pediatric palliative care team to start a tele-hospice program. This ensured that children in hospice care could continue to receive compassionate support remotely. 

"All of the providers who cared for Oliver learned so much from him and his family, including how helpful it was to have real-time video assessment of patients with challenging pain and symptoms during in-home hospice visits by nurses," says Christopher Collura, M.D., the medical director of Pediatric Palliative Care (ComPASS) at Mayo. "This inspired our team to formalize a tele-hospice program in order to streamline assessments by pediatric palliative medicine physicians for children enrolled with Mayo Clinic Hospice." 

Honoring Oliver and Welcoming His Baby Sister 

Throughout Oliver's life and even in his final hours, Dr. Thompson and her team formed a tight, supportive relationship with Oliver and his family, providing comfort and care when it was most needed. 

"Dr. Thompson was really there for us during the hardest time of our lives. And she has continued to support us after Oliver's death," Justine says. "Every year she joins us to honor his memory at our balloon release on Oliver's birthday." 

The Bates family also reached out to Dr. Thompson for guidance on the potential for having another child. 

WOREE syndrome, the genetic condition that affected Oliver, is a recessive disorder. That means both parents carry a copy of the mutated gene but usually show no symptoms. Each pregnancy has a 25% chance of the child inheriting two defective genes — one from each parent — which leads to the disease. Using these genetic insights, Dr. Thompson helped guide the Bates family to the subspecialists who helped them choose a plan that would increase the likelihood of a healthy pregnancy unaffected by the same genetic condition that Oliver had. 

In May, Oliver's legacy was further celebrated with the birth of his baby sister. Justine and Casey named her Whitney, in tribute to Dr. Thompson, reflecting their deep gratitude for the care and dedication Dr. Thompson gave to Oliver and their family. 

"I am deeply touched by this gesture," Dr. Thompson says. "Oliver's story shows us that new beginnings can coexist with cherished memories to help provide healing and comfort."

This article was originally published in Mayo Clinic News Network. 

The post Baby Oliver Leaves Legacy of Genomic Advances at Mayo Clinic appeared first on Mayo Clinic Magazine.

“It's the most deadly — the least survivable — of all cancers that we know of,” says Mark Truty, M.D., surgical oncologist at Mayo Clinic. “That's what makes it such an awful disease to deal with.” 

But what if there was a way to catch it early, before it spreads and becomes harder to treat? Artificial intelligence (AI) is giving medical professionals a new edge in early detection of pancreatic cancer — and offering hope for patients who once had few options. 

Mayo Clinic radiologist and nuclear medicine specialist Ajit Goenka, M.D., says it’s the responsibility of medical imaging experts to develop better detection methods and technology that can catch pancreatic cancer at its earliest possible stage.  

“To be able to detect and identify disease at a stage where it is beyond the capabilities of human perception, that’s really the holy grail of medicine,” Dr. Goenka says. 

AI’s Role in Early Pancreatic Cancer Detection

AI programming can help by pinpointing tumors with much higher resolution than the human eye.  

“What AI is really good at is quantifying very subtle changes that happen on the images that human beings cannot pick up due to the inherent limitations of their eyesight,” Dr. Goenka says. 

This ability to detect even the smallest variations in scans allows for faster and more accurate diagnoses, which can significantly improve patient outcomes. 

“If you were to ask me right now to sit down on a state-of-the-art computer and try to segment the pancreas, it would take me anywhere from 20 to 30 minutes, and I might still not be accurate,” Dr. Goenka says. “In contrast, the AI models that we have trained can do that job in a fraction of a second. And not only that, they can do that for thousands of CT scans without requiring any kind of manual input.”

To be able to detect and identify disease at a stage where it is beyond the capabilities of human perception, that’s really the holy grail of medicine.

— Ajit Goenka, M.D.

AI’s ability to detect pancreatic cancer earlier than traditional methods offers a critical advantage. The earlier the cancer is identified, the sooner treatment can begin, which dramatically increases the chances of survival. 

“What we have seen is that AI can help us diagnose pancreatic cancer almost a year before its clinical presentation,” Dr. Goenka says. 

That head start can make a significant difference: According to the American Cancer Society’s Cancer Facts & Figures 2024 report, the five-year survival rate for pancreatic cancer is currently 13%. When detected early, confined to the pancreas and treated accordingly, the five-year survival rate increases to 44%. 

The Future of AI and Cancer Care

By shifting the timeline of diagnosis, AI offers a chance to rewrite survival stories in pancreatic and other forms of cancer. According to Dr. Truty, patients whose survival was once measured in months or just a couple of years could go on to live "many years and hopefully decades,” he says — and, ultimately, reach a cure. 

“There is definitely hope on the horizon,” Dr. Goenka says. “We just have to make the right kind of effort and use cutting-edge technologies like AI to make that dent in this disease.”

This research was supported by the Hoveida Family Foundation.

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Engineering Earlier
Cancer Detection
Through AI

Bahman and Becky Hoveida believe in a future of healthcare where cancers are diagnosed earlier, at a stage when treatments are less taxing and the chance of survival is greater. Learn how their generosity is accelerating Mayo Clinic's bold vision to revolutionize cancer care.

Read More

The post Unlocking AI’s Potential in Early Pancreatic Cancer Detection appeared first on Mayo Clinic Magazine.

How Automation Gives Back One of Healthcare’s Most Valuable Resources – Time

Intelligent automation — a blend of artificial intelligence, digital tools and robotics — is already easing administrative burdens and improving patient access to care. In this article first published on the World Economic Forum website, Gianrico Farrugia, M.D., president and CEO of Mayo Clinic, highlights the need for collaboration among providers, government agencies and tech companies to enhance patient outcomes and staff well-being.

Within healthcare, there are few, if any, resources more precious and closely managed than time. As many healthcare providers worldwide will tell you, there is simply not enough time to care for all their patients with quality and compassion and, simultaneously, complete mandatory tasks, such as record reviews, documentation and insurance paperwork. Globally, the source of this problem is twofold: an ongoing shortage of healthcare workers, including nurses, physicians and all allied health staff, and an increase in demand due to an aging global population with growing healthcare needs. Both are compounded by an antiquated underlying architecture in healthcare that inhibits innovation and transformative solutions. 

Highly developed countries are not immune from these challenges. In the U.S., the shortage is expected to reach 187,000 physicians and 63,000 registered nurses in the coming decades, with even more staff needed to meet unaddressed healthcare issues. In France, more physicians are retiring than starting their practice. In England, 10% of nursing and 7% of physician positions are vacant, while less than a third of National Health Service staff feel their hospital is adequately staffed to provide excellent care. Even before the COVID-19 pandemic, many patients around the world saw longer and growing wait times for care. 

At the same time, digital tools intended to create greater efficiency and save time have, in some cases, become an added source of administrative burden for care teams. With doctors reporting a nearly 60-hour workweek in a physically and mentally demanding profession, it is little wonder that almost 50% also report at least one symptom of burnout. 

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Fixing Healthcare’s Time Constraints Requires Innovative, Platform-Based Solutions 

While we must revamp and shorten educational curricula to recruit and train more healthcare workers, hiring and training alone cannot solve this global shortfall of healthcare workers. Healthcare organizations — alongside governments and other agencies — must find innovative ways to reduce the administrative burden, while expanding access to lifesaving care and expertise to patients in need. 

We have previously advocated for a global move to a platform model of healthcare. As part of that move, few tools have shown as much promise to address these problems as intelligent automation, a combination of digital tools, robotics and AI that streamline or even eliminate human involvement in administrative processes. When these tools are deployed within a platform model of care, we have already seen how they can reduce healthcare workers’ overall workload, while providing greater access for patients. 

In addition, the next generation of powerful emerging AI tools — particularly agentic AI, a dynamic class of AI that can autonomously carry out tasks with high fidelity — is expanding what was previously possible by creating automated AI tools that are dynamic, responsive and adaptable to each user’s needs. Agentic AI — paired with existing automation technology — has the potential to streamline administrative tasks while extending healthcare workers’ expertise to reach more patients without additional strain, enabling the most essential task of any healthcare system: providing direct care to patients. 

Around the World, Health Systems Are Using Intelligent Automation to Save Time 

Because no nation or health system is immune to workforce shortages or time-constrained staffing, many are turning to innovative automation tools to streamline processes, improve worker experiences and make healthcare careers more attractive overall.  

In Taiwan, where a single-payer system with complex rules requires significant work to accurately submit expenses, researchers have used software robots to reduce the time it takes to complete these tasks by 31%. In the U.S., autonomous robotic vehicles deliver meals and pharmaceuticals in hospitals and clinics, freeing up care teams to focus on patients instead of time-consuming logistical details. In Belgium, AI-tools help streamline complex procedures, like cardiac catheterization, by analyzing imagery before and after procedures and prepopulating reports. Ghana, which faces a shortage of providers, particularly radiologists, is home to a tech startup that has developed an AI-powered diagnostic tool that is effective at diagnosing conditions like cardiomegaly and can do so more accurately than many trained professionals — expanding access to critical diagnostic care to patients while off-loading tasks from overstretched radiologists. 

At Mayo Clinic, our physicians and researchers have shown how AI-powered automation can save time while improving outcomes for head and neck radiotherapy. With our partners, we are also refining AI ambient listening technology to automate documentation for nurses, while robots are assisting in routine tasks, like linen delivery. Yet, it is also clear that we — and the entire global healthcare system — are just at the beginning of realizing the benefits of intelligent automation for our patients and staff. 

To Maximize the Impact of Intelligent Automation Tools, Healthcare Must Act Now 

As we look to the future, rapidly developing automation technology holds even greater potential to positively transform how healthcare workers provide care and how patients receive it. For example, fully realized agentic AI tools can provide personalized high-level services to patients, helping them navigate complex health systems and processes. For physicians and providers, these tools can likewise extend their expertise and insight through agentic digital twins that reliably and accurately answer patient questions on diagnoses, outcomes and results. Digital pathology and radiology platforms can extend the reach of urgent diagnostic services to underserved populations and even entire nations, while purpose-built infrastructure will allow for greater robotic automation of routine tasks. 

However, none of these possibilities are necessarily assured. While moving forward without a patient-centered approach is dangerous and will lead to harm, so is delaying moving forward to wait for complete clarity. Patients and healthcare workers need nonincremental solutions today. The health sector must, without delay, take ownership of this opportunity, lead in establishing codes of conduct for intelligent automation, and partner with automation innovators and government agencies to co-create solutions and develop pragmatic regulations. Patient and healthcare worker voices must remain central to how these tools are developed, validated and deployed into the healthcare workstream for the maximal and equitable benefit of all. The time to lead is now. 

The post How Automation Gives Back One of Healthcare’s Most Valuable Resources – Time appeared first on Mayo Clinic Magazine.