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.

Open image in lightbox

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.

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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.

Falling behind her siblings was an early sign of the condition that would soon shape her life. "I remember running after my brothers and I couldn't keep up. Then I would turn blue,” she says. 

Unfortunately, she wasn’t the only one in her family with heart problems. By her early teens, Kataliya experienced the devastating death of her younger sister, who passed away suddenly from a heart condition — a loss that underscored the urgency of Kataliya's own. From then on, her life became one of medications and caution, aimed at keeping her alive. 

Despite these efforts, Kataliya’s health began to decline in 2020. "I felt like I was suffocating," she recalls. That led her to Mayo Clinic, where she worked with transplant cardiologist Rohan Goswami, M.D., to find a lasting solution. 

Defying the Odds 

Kataliya had a difficult journey ahead of her. According to Dr. Goswami, the challenge in her case was twofold. First, she had a specific heart condition, hypertrophic cardiomyopathy, that elevated the risks associated with using any support devices. Additionally, she had a high level of antibodies in her bloodstream, further complicating her situation. 

“I came in at 97% antibodies, which means my systems would fight 97 out of 100 hearts,” Kataliya says. “Basically, I had a very small chance they could find a match [for a transplant]. How could they find that one heart of millions that I would not reject?” 

The Future of AI and Transplants 

Artificial intelligence (AI) is emerging as a powerful ally in organ transplantation, paving the way for safer and more effective outcomes. "It takes lots of patients over lots of treatment pathways and helps us identify the best one for the person sitting in front of me,” Dr. Goswami says.

Kataliya’s case is a prime example. According to Dr. Goswami, AI added a new dimension in helping her medical team understand her risks and gauge her potential for a successful match before her transplant. But that’s only scratching the surface of AI’s transformative role in transplantation. 

"I think organ matching, patient survival and also looking at the ability to predict who's a high-risk or a low-risk patient are going to change the landscape of transplant in the next couple of years,” says Dr. Goswami. 

At Mayo Clinic, research is already underway to explore the full potential of AI’s capabilities in transplantation. Dr. Goswami explains that advanced algorithms are helping researchers “understand and identify the factors that may be playing a more significant role in a patient's risk for infection, cancer or rejection” — insights that extend far beyond the traditional models clinicians have relied on for over 20 years. 

"We are using AI to redefine our understanding of chronic disease, potentially preventing the need for organ replacement therapy altogether,” he says. 

Living Life Out Loud 

On June 6, 2023, Kataliya got her perfect match. 

After receiving her life-changing transplant, she could, as she puts it, finally start "living life out loud." She even began running — an achievement that had previously seemed completely out of reach. "It feels very powerful," she says. 

We are using AI to redefine our understanding of chronic disease, potentially preventing the need for organ replacement therapy altogether.

— Rohan Goswami, M.D.

For Kataliya, AI was more than just a technology — it was a lifeline. Thanks to the power of AI and her team's experience, she’s living a life she once thought impossible. And for the future of transplant patients, AI offers the hope of a similar second chance.

The post AI’s Role in Kataliya’s Heart Transplant Journey appeared first on Mayo Clinic Magazine.

Time Is Brain

In stroke care, time is brain.

From the moment a stroke begins until clinicians have restored normal blood flow in the brain, the clock is ticking. Every minute can mean the death of millions of neurons — our brain’s fragile, critical cells that control our every function. But it takes time to determine if a patient is experiencing a stroke and, if so, what kind of stroke they are having, before any treatment can be given. When it comes to improving stroke care, anything that can speed up the process of identifying and addressing the condition can have an enormous impact on patient recovery.

Enter: Artificial intelligence (AI). At Mayo Clinic, clinicians are using AI algorithms to speed up stroke detection and diagnosis and coordinate care teams to get patients the treatment they need sooner, saving millions of brain cells and improving patient outcomes.

A Ticking Clock

For Sophia Chan, that clock started ticking at approximately 2:05 on a Thursday afternoon in February 2022. It was just another day at her high-pressure job as a television producer when she began to experience a severe headache.

She explains that she doesn’t remember what happened that day — she only knows what she’s heard from her husband and the first responders. “Normally I would just go lie down for a bit and hope for the headache to go away,” Sophia says. “Apparently that day I did end up calling for help, and that’s what saved my life.”

By the time the first responders arrived just minutes later, she was unresponsive. She’d suffered a brain aneurysm while she was home alone. She was transported to Mayo Clinic in Jacksonville, just 15 minutes away.

While Sophia can’t remember anything from that day, her husband, Bobby Cullen, remembers it all in vivid, painful detail, recalling how he spoke to her just hours before a neighbor texted to ask about the ambulances outside their house.

He had been out of town for work, and it took him five hours to get back home. By the time he arrived, Sophia had already been in and out of surgery, and her status was still so tenuous that he wasn’t allowed into her room. He was finally allowed to see her in the earliest hours of the morning, when a clinician told him that it was time to say goodbye — Sophia wasn’t expected to survive for much longer. “I stood by her head for the next eight hours,” Bobby says. “The doctors tried to tell me to sit down, but I told them I wouldn’t sit down until she’d taken her last breath.”

Those eight hours turned into 36 hours, then 72. “On day 7, one of the doctors told me that I should go home and take care of myself,” says Bobby. Sophia continued to beat the odds, but she wasn’t out of the woods. It took almost three weeks for her care team to fully stabilize her condition. She can’t remember anything that happened during the first 21 days of her hospitalization.

Accelerating Diagnosis and Intervention

William Freeman, M.D., is focused on developing systems to better recognize and treat hemorrhagic strokes like Sophia’s, which are less common but often more debilitating than ischemic strokes. This is because ischemic strokes are the result of a blocked blood vessel, which leads to brain tissue injury as the cells are deprived of oxygen. Hemorrhagic strokes, caused by a ruptured blood vessel, result in rapid tissue damage as blood pools and increases pressure in the brain.

The treatments for the two types of strokes are different. Treatment for an ischemic stroke involves breaking up the blood clot, either with a medication or mechanically, so the blood can flow again. Hemorrhagic strokes are treated by providing medications to reverse any blood thinners the patient may be on, stop the bleeding, and relieve pressure on the brain to reduce tissue damage.

Knowing which kind of stroke a person is having is very important for choosing the right treatment. The wrong treatment could make a patient’s condition worse.

With the help of AI, a process that once could take half an hour or longer can now take just seconds. When a patient enters the emergency department with a suspected stroke, the first critical step is getting them a CT scan, generating detailed images of the patient’s brain using X-rays. Technicians then review the images looking for abnormalities in the brain to determine the location of the stroke and what type of stroke it is.

Now, an AI algorithm trained on a database of CT images from patients who have had strokes can rapidly scan hundreds of images and pull out the ones showing an abnormality. A technician reviews the relevant images and confirms the algorithm’s assessment. “A full CT and CT angiogram can be up to about 1,200 pictures,” says Dr. Freeman. “And before the software came into play, we’d be looking manually, slice by slice. It seems like it takes an eternity. AI can compress all those minutes down into seconds.”

After diagnosis comes intervention. Once the stroke has been located and clinicians determine its type, a care team is gathered to initiate the appropriate treatment. Dr. Freeman says AI can smooth this process too by sending automated messages to on-call clinicians as soon as a diagnosis is reached.

“Now, I’ll be in the CT control room, and while a technician is still processing the images, my smartphone pops up with a notification telling me that it’s go time,” he says. “It’s really a sight to behold.”

42 Million Neurons Saved With AI Intervention

30 MINUTES

Patient experiences ischemic stroke symptoms, such as slurred speech, numbness or weakness on one side of the body, or a sudden severe headache.

+20 MINUTES

EMT services are called for the patient, and patient is transported to hospital by EMTs.

+10 MINUTES

Patient arrives at hospital and is triaged in the emergency department. Care team suspects a stroke, and the patient is sent for a CT scan.

+10 MINUTES

Patient undergoes CT scan, and images are sent for review.

WITHOUT AI INTERVENTION

+25 MINUTES

CT images are manually reviewed by a technician to identify the stroke site and type. Care team is gathered to provide treatment. Patient receives treatment for stroke and begins the recovery process.

TOTAL TIME: 95 MINUTES

TOTAL NEURONS LOST: 180.5 MILLION

WITH AI INTERVENTION

+3 MINUTES

CT images are run through AI algorithm to identify stroke site and type. AI system alerts care team and directs them to the patient for treatment. Patient receives treatment for stroke and begins the recovery process.

TOTAL TIME: 73 MINUTES

TOTAL NEURONS LOST: 138.7 MILLION

The Difference a Minute Can Make

While AI tools have been well studied in ischemic stroke, they are less developed for use with hemorrhagic stroke, and that’s what Dr. Freeman wants to change.

“In a hemorrhagic stroke, patients get super sick, super fast,” he explains. “We estimate that patients lose between 6 million and 8 million brain cells per minute in just the first two hours. AI can help get patients out of the waiting room and into treatment much faster.”

Research has found that integrating AI into care for an ischemic stroke can save an average of about 22 minutes. With an estimated 1.9 million neurons lost during every minute of an ischemic stroke, this adds up to about 42 million neurons saved. With even more neurons lost per minute in hemorrhagic stroke, saving even just 10 minutes could have a dramatic impact on a patient’s recovery.

This technology, along with training and teamwork, is already having an impact in the clinic. “With AI implementation, we’re absolutely seeing a difference,” says Kacie Brewer, P.A.-C., who is a member of Sophia’s care team. “It’s getting patients the care they need faster by speeding up the diagnosis and pulling together the right team as quickly as possible.”

Sophia is acutely aware of the importance of those 10 minutes. Her proximity to Mayo Clinic and the AI algorithms that allowed the care team to find her aneurysm in minutes are likely the keys to her remarkable recovery. “I feel very fortunate to have been near Mayo Clinic,” she says. “The care I received was the best of the best.”

Her treatment at Mayo Clinic did more than just save her life. Many who survive hemorrhagic strokes go on to have significant lifelong disabilities. Two years after her stroke, Sophia is thriving, getting back to her active lifestyle of chasing around her sporty 9-year-old twins and easing into her yoga practice.

The family has moved to California to be closer to family, but still travels back to Jacksonville for follow-up visits.

Sophia’s case is remarkable because it’s still not yet the norm — most patients who suffer a hemorrhagic stroke do not experience a recovery like hers. Dr. Freeman believes that better AI algorithms and implementations, along with other cutting-edge technologies, can change that.

Sophia is now participating in the DISCOVERY study, a clinical trial leveraging Mayo Clinic’s expertise in neurology and neuroimaging to understand the risks of post-stroke cognitive impairment in diverse populations. She hopes that the research can lead to better outcomes for other patients like her.

And, every year, she and Bobby make a special effort to send treats and thank each of the doctors and nurses who provided so much of the care and support their family received during those first few impossible weeks.

“We really believe in Mayo Clinic’s values and mission,” says Bobby. “We could see how all of Sophia’s care was really a group effort, and it saved her life.”

The post Time Is Brain appeared first on Mayo Clinic Magazine.

Dr. Shah has a distinguished 25-year career in National Institutes of Health-funded research on advanced liver disease. He brings expertise in basic science, artificial intelligence and clinical trials to this pivotal role. Mayo Clinic Magazine had the opportunity to discuss what led Dr. Shah to this position and his vision for the future of research at Mayo Clinic.

How do you balance and integrate your research responsibilities with clinical and leadership duties in your current role?

I focus a lot on creating a vision to work toward with my team and then supporting them so that our team members can all work together and support one another. I also want them to feel safe coming to me for help when they need it. I have so much gratitude for all the people who have helped me in my career, and I’m thankful to be able to support so many others through my leadership duties.

I’m thrilled to now be in the position of leading the Research shield at Mayo Clinic. At Mayo, our research and practice are intertwined. My medical practice helping patients each and every day connects directly to our expansive research program aimed at finding solutions that don’t exist today. Ultimately, building trust and creating supportive teams means that we can all work together to focus on our primary value: putting the needs of our patients first.

What brought you to Mayo Clinic?

It was serendipity. While I was doing my fellowship at Yale, my wife took a position in the Twin Cities. During that time, I came to Mayo for a month to do a transplant rotation, and that made all the difference for me. I met a lot of role models here at Mayo — Drs. Nick LaRusso, Greg Gores, Russ Wiesner. They introduced me to Mayo Clinic and demystified it for me.

When I had this chance to visit and to meet the people here, I saw that it was somewhere that would be a great fit for me and my work. Rochester has a wonderful mix of small-town charm and all the cosmopolitan aspects of a large intellectual city. It’s been a great place to raise kids, and Mayo Clinic has been an amazing place to work. It’s a testament to why I’ve been here for 25 years.

Our digital transformation is allowing us to better organize our data and apply algorithms to gain new insights into disease.

What excites you the most about the future of research at Mayo?

At Mayo Clinic, our research is about finding new cures for patients, especially for serious or complex diseases. That’s the principle that drives everything we’re doing. And from that, there are so many ways now that we can find new cures. We have our traditional pathways, led by our immensely talented research investigators — work in the lab discovering new insights into the biology of disease, designing and testing new therapies for treating those diseases, and bringing those new treatments into the clinic for patients.

Now we have many other ways, like Mayo Clinic Platform, where we can start to utilize patient data from around the world to reimagine how we do clinical trials. Artificial intelligence can speed up the pathway to drug discovery. Our digital transformation is allowing us to better organize our data and apply algorithms to gain new insights into disease. These are just some of the pathways that will help us get to more cures. All of these tools are accelerating the pace of research, and in turn the pace of treatments, and all of that will mean our patients get better therapies faster than ever before.

The post Reimagining the Future of Research With Vijay Shah, M.D. appeared first on Mayo Clinic Magazine.

It also affected her vision in an indirect way, making it difficult for her to process visual signals, yet she thought she was “fine.” “With cortical blindness, you can’t see, but you don’t know it,” Dr. Jones says. “None of her caregivers realized she couldn’t see. In my practice, I see that same sequence of events, leading from mild memory syndrome to denial to cortical blindness. It’s easy to predict how the brain will look in those cases.”

After receiving his M.D. in neurology years later and starting his research lab, Dr. Jones named a phenotype of the disease after his grandmother, the “MFB variant.” The name is used internally for teaching purposes.

A Human Touch

For decades, Alzheimer’s and dementia have been the subjects of intense study. Today, Dr. Jones and researchers of his caliber can recognize brain changes as neurodegenerative conditions progress. By spotting patterns linked to a particular condition, healthcare professionals can identify dementia before symptoms become clinical, allowing early interventions.

But there are limits to what even the world’s top scientists can observe — limits that Dr. Jones is helping overcome as the director of artificial intelligence in the Department of Neurology at Mayo Clinic. Dr. Jones heads the Neurology Artificial Intelligence Program (NAIP), which helps clinicians diagnose neurological disorders through pattern recognition.

A significant advantage of artificial intelligence (AI) is its ability to find patterns in datasets with more inputs than any physician can consider. AI doesn’t replace human knowledge or physician expertise — it strengthens them.

“If physicians are aided by a technology that tells them about a pattern, they can provide better care,” Dr. Jones says. The Mayo Clinic Cloud includes some 16,000 brain images dating back about 15 years. That’s a lot of fodder for pattern recognition.

Dr. Jones sees a parallel between how physicians think when diagnosing and the work of his NAIP team. Physicians traditionally use tests and questions to spot patterns that fit what they know and have observed about diseases. AI does this too, but faster and with the ability to capture a vastly larger quantity of data. In building the NAIP’s tools, Dr. Jones and his team strive to capture that synergy.

“When we consult experts for diagnosis, they often tell a story about the outcome of a case where a patient had a particular feature,” he says. “That’s usually what solves the problem. The algorithm digitizes that process.”

Working with AI has clarified Dr. Jones’ thoughts about brain aging and degeneration and vice versa.

If physicians are aided by a technology that tells them about a pattern, they can provide better care.

“You want AI to recognize patterns, to speak and to reason. Degenerative diseases can take those abilities away from people,” he says. “All these things that we want to build into AI systems are things brains do. So they all inform each other.”

A Change of Direction

Little did Dr. Jones know early in life that his route would take him to the intersection of the human mind and AI. Instead, he trained as a thespian in high school, receiving a theater scholarship. But two transformative moments planted a seed in Dr. Jones’ life.

The first came when he went to a bookstore and accidentally purchased a copy of “Gödel, Escher, Bach: an Eternal Golden Braid,” by Douglas Hofstadter and decided to read it anyway. The 1979 Pulitzer Prize-winning nonfiction book wove together music, art, math and the then-distant possibility that AI could mimic human thought.

The second inclination of his fascination with the human mind came from a script he helped write based on characters from “The Man Who Mistook His Wife for a Hat,” by Oliver Sacks.

Dr. Jones played a person who lacked awareness of the body’s position in space, known as proprioception.

“I actually didn’t understand the condition at the time, so I didn’t play the role very well,” he recalls.

A Shift to Science

It was at Georgetown University that he became fascinated with neuroimaging and brain networks. He grasped the immense potential of machine learning technology and its ability to detect patterns.

After medical school, Dr. Jones joined Mayo Clinic and worked in the brain-imaging and cognitive-aging laboratory of Clifford Jack Jr., M.D., which further brought his scientific passions into focus.

From the day he arrived at Mayo, Dr. Jones has taken Mayo’s core value to heart: “The patient’s needs come first.” This value, he says, guides his teams in building systems that work well for patients.

“Physicians at Mayo now stand shoulder to shoulder with data scientists and software engineers. We understand enough about each others’ disciplines to speak a common language as a care team,” says Dr. Jones.

Dr. Jones is working toward a compassionate way to predict multiple neurological disorders based on a single brain scan. The current diagnostic process often requires numerous blood samples and other uncomfortable procedures. The new method offers many advantages to the patient: less travel, less time and expense, less invasive measures, and an earlier diagnosis.

Brain scans are just the beginning of AI’s usefulness. Dr. Jones sees a future where other diagnostic data can be digitized and overlaid on the same platform. That includes videos, voice samples, eye tracking, cognitive tests and more.

And who better to leverage AI than an organization world-renowned for its patient-centered approach? “Change should be led by people who understand the patient’s needs,” says Dr. Jones. And shoulder to shoulder, his multidisciplinary care team does just that.

Change should be led by people who understand the patient’s needs.

The post A Cognitive Compass: AI and the Aging Brain appeared first on Mayo Clinic Magazine.