Mayo Clinic’s Berg Innovation Exchange and Business Development unite expertise in collaboration, commercialization and venture creation to accelerate innovation worldwide

ROCHESTER, Minn. — Mayo Clinic is strengthening its commitment to advancing healthcare innovation by aligning the Mayo Clinic Berg Innovation Exchange with Mayo Clinic Business Development, creating new opportunities to help promising discoveries reach patients and communities worldwide.

Since its launch, the Berg Innovation Exchange has connected innovators with expertise, mentorship and a global network of collaborators. The exchange has served as a catalyst for innovation within Mayo Clinic and across the broader healthcare ecosystem, bringing together clinicians, researchers, entrepreneurs, industry leaders and investors to explore new approaches to healthcare challenges.

The alignment with Business Development creates stronger connections between early-stage innovation activities and the expertise needed to advance technologies, launch new ventures and expand the reach of Mayo Clinic discoveries.

"From the beginning, the vision of the exchange has been to help innovators find the expertise and opportunities needed to move ideas forward," says Jennie Kung, vice chair of Mayo Clinic Berg Innovation Exchange. "What started as a vision for accelerating innovation has grown into a community of innovators and problem-solvers and positions us to support even more meaningful work in the years ahead."

The exchange helps innovators refine and validate new concepts by providing access to collaborators’ collective expertise. Business Development complements those efforts through capabilities in intellectual property, licensing, venture creation, investment activities and commercialization.

Together, these capabilities create a more seamless pathway from discovery to real-world application, helping promising innovations advance toward broader adoption and patient impact.

"Innovation depends on strong connections between discovery, commercialization and collaboration," says Andy Danielsen, chief business development officer at Mayo Clinic. "This alignment expands opportunities to work with organizations around the world and provides the resources needed to translate ideas into products and services that benefit patients."

As healthcare continues to evolve, Mayo Clinic is committed to fostering relationships and collaborations that help advance innovation beyond institutional boundaries. Earlier access to expertise and strategic guidance can help innovators navigate key decisions and identify the most effective path forward.

"The ultimate measure of innovation is whether it makes a difference in people's lives," says Peter Noseworthy, M.D., medical director for Business Development. "Strengthening the connection between innovation and commercialization helps promising discoveries gain traction beyond Mayo Clinic and creates more opportunity for impact."

The exchange will continue to play an important role in identifying opportunities, encouraging collaboration and helping innovators transform promising ideas into meaningful advances.

At its core, the effort reflects Mayo Clinic's belief that meaningful progress happens when people with diverse expertise come together to solve important challenges.

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About the Berg Innovation Exchange
Supported by philanthropic funding, the Berg Innovation Exchange operates with impartiality, ensuring equal opportunities for all innovators and stakeholders, with an emphasis on addressing healthcare needs over individual or institutional interests.

About Mayo Clinic 
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Tom Millikin, Mayo Clinic Communications, newsbureau@mayo.edu

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Healthcare AI is evolving beyond predicting outcomes to helping clinicians and researchers make informed decisions.

This shift was a key focus of Mayo Clinic's AI Research Summit, where more than 750 researchers, clinicians, AI scientists, engineers, students and other innovators gathered June 4–5 in Rochester, Minnesota, and online.

"The future of healthcare AI is not simply about building better predictor models, it's about developing integrated decision intelligence systems," said Cui Tao, Ph.D., the Nancy Peretsman and Robert Scully Chair of AI and Informatics at Mayo Clinic.

The summit highlighted emerging approaches such as multi-agentic AI, in which multiple agents work together on complex tasks, and simulations that use real-world data to test ideas and generate insights faster.

Helping personalize patient care

A key application of healthcare AI is personalized decision support at the point of care.

Yong Chen, Ph.D., of the University of Pennsylvania, said clinicians need tools that go beyond prediction to help them determine which actions will lead to the best patient outcomes.

Healthcare is a sequence of interconnected decisions that evolve over time — which treatment to use, when to intervene and when to adjust care. Integrated AI tools could help care teams determine the optimal next step for each patient.

For example, when patients receive an implant such as a stent, personalized decision-making support systems could help clinicians determine the best timing for antiplatelet therapy while reducing the risk of complications.

Changing how discoveries are tested

AI and automation may help researchers accelerate the discovery and testing of new medical treatments, said Matt Redlon, chair of the AI Program and vice president of Digital Biology, Mayo Clinic Digital Pathology.

For many diseases, thousands of existing drugs could be studied for potential repurposing, said Redlon.

Multi-agentic AI systems could be used to simultaneously analyze data from multiple sources such as biospecimens and clinical records, helping researchers identify the most promising treatments for further study. Researchers also are exploring virtual trials, which use AI and existing healthcare data to simulate clinical trials, as a strategy to generate early signals from real-world data. This could substantially shorten the timeline for assessing promising new therapies for patients.

Watch: Mayo Clinic summit highlights shift in healthcare AI research

Journalists: Broadcast-quality sound bites are available in the downloads at the bottom of the posts. Name super/CG: Cui Tao, Ph.D./Nancy Peretsman and Robert Scully Chair of AI and Informatics at Mayo Clinic/Mayo Clinic/Matt Redlon/Chair of AI Program, Vice President of Digital Biology in Digital Pathology/Mayo Clinic/Micky Tripathi, Ph.D./Chief AI Implementation Officer/Mayo Clinic

Supporting clinicians and researchers

In addition to delivering more personalized care, AI technologies are being developed to streamline work for healthcare staff.

Some solutions are designed to augment human capabilities by "doing things that humans literally can't do with the limitations of our senses," said Micky Tripathi, Ph.D., chief AI implementation officer at Mayo Clinic.

For example, researchers have developed AI models that can help clinicians detect pancreatic cancer early from routine abdominal scans before tumors are visible.

Building the foundation for responsible AI

Peter Lee, Ph.D., president of Microsoft Science, emphasized that AI in healthcare has rapidly moved from idea to infrastructure, with solutions such as ambient tools that capture data in patient care now widely used.

As these capabilities expand, healthcare organizations must build the governance, oversight and supporting infrastructure needed to deploy technologies safely, responsibly and reliably.

Tripathi compared this to building a car. "You defined an engine; that's great. But it doesn't have a chassis, doesn't have a steering wheel, doesn't have windshield wipers, it doesn't have lights," he said. "We need all of those things."

Speakers emphasized that human oversight remains essential, with clinicians and researchers responsible for evaluating information and making final decisions.

"The momentum is clearly growing," Dr. Tao said. "If AI is going to become a part of real clinical care, we need rigorous validation, a governance framework, workflow integration and translational maintenance. And that translation from innovation to responsible implementation is exactly where the field is heading next."

Other experts, including Yi Qian, vice president of Global Real World Evidence at Johnson & Johnson, highlighted approaches to creating trusted evidence and insights for clinical care.

Related

• Mayo Clinic and Microsoft collaborate to develop a frontier AI model for healthcare 
• How researchers are using AI to accelerate the path to cures (VIDEO)
• How 60 years of health data helped shape modern medicine

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ROCHESTER, Minn. — Mayo Clinic Platform_Accelerate has selected 20 healthcare technology startups to join its accelerator program. Through an immersive 30-week program with a structured curriculum, companies collaborate with leading experts, receive one-on-one technical mentorship, and work with Mayo Clinic Platform's de-identified clinical data ecosystem to advance the development of their digital health solutions.

"The Accelerate program serves as an engine for digital health breakthroughs, offering technology startups resources and expertise to build solutions for long-term impact," says John Halamka, M.D., Dwight and Dian Diercks President of Mayo Clinic Platform. "The digital health solutions represented in this cohort reflect a broader shift in healthcare from experimenting with artificial intelligence (AI) to deploying AI at scale. These innovations have the potential to help healthcare organizations advance patient care, enhance operational efficiency and unlock new ways of supporting patients and clinicians."

The 20 startups participating in the June cohort are working to address complex healthcare challenges.

• Aquoris Intelligence is developing an AI-powered clinical reasoning platform that helps physicians navigate diagnostic complexity, treatment decisions and longitudinal patient context through clinician-centered decision support.
• Burna AI automates evidence-based adverse event grading and coding across the clinical research continuum, improving data quality, operational efficiency and oncology trial execution.
• Cardiolife delivers AI-enabled electrocardiogram (ECG) and Holter monitor interpretation that supports scalable, clinically validated cardiovascular diagnostics while integrating seamlessly into existing care workflows.
• Caremaze uses AI-driven discharge coordination to identify barriers early, streamline multidisciplinary workflows and help health systems reduce length of stay while improving care team efficiency.
• Dr. Data's APEX platform combines clinical guidelines, imaging, digital twins, and real-world evidence to generate transparent, evidence-grounded cardiovascular treatment recommendations.
• éo-vision AI uncovers clinically meaningful signals hidden within medical imaging to support more informed decision-making across healthcare delivery, payer operations and drug development.
• HealMint integrates multimodal AI, continuous biometric monitoring and clinical-grade devices to enable proactive, predictive care for high-risk patient populations.
• Healthier is building an AI-native clinical reasoning platform that synthesizes complex oncology data into source-grounded insights for patients, clinicians and multidisciplinary care teams.
• Immunara leverages biological foundation models and multimodal data to advance precision immunology and uncover new insights into immune-mediated disease.
• InformAI develops AI-powered oncology solutions that accelerate radiation therapy planning and support more efficient, data-driven cancer care delivery.
• Maverick Medical AI automates clinical documentation, coding and revenue integrity workflows to improve reimbursement accuracy and reduce administrative burden at the point of care.
• MICA AI Medical is advancing breast cancer detection through AI-enhanced mammography analysis designed to improve diagnostic accuracy for patients with dense breast tissue while reducing reliance on supplemental imaging.
• Odesso combines clinical AI and intelligent automation to improve risk adjustment, quality performance and value-based care operations through highly accurate clinical data extraction.
• PeriMind applies AI-driven perioperative decision support and revenue optimization to improve surgical workflow efficiency, patient safety and financial performance.
• Plexis AI provides the governed execution infrastructure that enables health systems to safely operationalize AI agents across clinical and operational workflows.
• PrecXIMed is creating an AI-powered neuro-oncology platform that connects imaging analysis, surgical planning and remote monitoring to support coordinated, data-driven brain tumor care.
• Rette AI uses agentic AI and clinical intelligence to automate complex orthopedic revenue cycle processes while improving documentation accuracy and reducing denials.
• Summit Health Data automates clinical data abstraction and applies advanced analytics to accelerate research, improve operational efficiency, and support innovation in cellular therapy and transplant programs.
• SyncVR Medical scales immersive care through enterprise extended reality (XR) solutions that help health systems improve patient experience, reduce procedural anxiety and enhance clinical efficiency.
• ThinkBio.AI transforms complex biological and clinical data into actionable insights that support drug development, translational research and precision healthcare decision-making.

"The Accelerate team designed a program for visionary startups ready to transform healthcare," says Jamie Sundsbak, director of the Accelerate program. "We now offer multiple ways to participate through a 30-week immersive program or a multiyear engagement pathway."

Since its launch in 2022, the Accelerate program has welcomed more than 120 companies from around the world. To learn more about the program or to apply for an upcoming cohort, visit Mayo Clinic Platform_Accelerate.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Mayo Clinic Platform
Mayo Clinic Platform is a strategic initiative of Mayo Clinic that enables collaboration, data-driven innovation and responsible AI development to transform healthcare globally. Mayo Clinic Platform is reimagining healthcare as an ecosystem — one where data, digital solutions and expertise flow seamlessly between innovators and care teams to improve care for patients everywhere. 

Media contact:

• Caroline Auger, Mayo Clinic Communications, newsbureau@mayo.edu

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JACKSONVILLE, Fla. — Mayo Clinic researchers have identified a previously unrecognized way the kidneys regulate water balance — an advance that could lead to improved treatments for polycystic kidney disease (PKD) and other disorders. The study, led by Fouad Chebib, M.D., a nephrologist at Mayo Clinic, is published in the Journal of Clinical Investigation.

The findings build on decades of scientific understanding by revealing an additional pathway the kidney uses to control water balance. Until now, the body's ability to concentrate urine — and prevent dehydration — has been thought to depend primarily on the hormone vasopressin. Dr. Chebib's team discovered an alternative mechanism that operates independently of that system.

"The kidney's ability to regulate water is one of the most fundamental processes in the body," Dr. Chebib says. "It's not every day that you uncover a new way it carries out that function."

Polycystic kidney disease is a common inherited condition that causes fluid-filled cysts to grow in the kidneys over time, gradually reducing kidney function and often leading to kidney failure. It affects millions of people worldwide, including an estimated 140,000 people in the U.S. with the most common form, autosomal dominant PKD (ADPKD). Many patients eventually require dialysis or a kidney transplant.

Watch: 1940s-era drug shows new promise for kidney disease

Dr. Chebib's team studies how kidney cysts grow in PKD using lab-grown cell models. As part of that work, they tested compounds expected to worsen the disease process by increasing cellular signals linked to cyst growth. One of those compounds was probenecid, a drug first used in the 1940s to conserve limited supplies of penicillin by reducing its urinary excretion.

"We thought this drug would make the disease process worse," Dr. Chebib says. "Instead, it did the opposite."

Rather than promoting cyst growth, the drug slowed it. After repeating the experiments multiple times, the team realized they had uncovered something important.

Further investigation revealed that probenecid affects how kidney cells handle urate, a molecule commonly associated with gout. Inside the cell, urate acts as a signal — triggering a chain of events that helps move water channels to the cell surface. This allows the kidney to reabsorb water and concentrate urine without relying on vasopressin, the hormone traditionally thought to control this process.

"This represents a distinct pathway from what is described in traditional physiology models," Dr. Chebib says. "It demonstrates that the kidney has an additional mechanism to preserve water."

For patients with PKD, the discovery could address one of the biggest challenges of current treatment. The only approved therapy, tolvaptan, works by blocking vasopressin, which slows cyst growth but causes patients to produce very large amounts of urine — often 6 to 7 liters a day. That side effect can be difficult to live with and leads some patients to stop treatment.

In preclinical studies and a small clinical trial, adding probenecid reduced urine volume and nighttime urination while preserving the treatment's effectiveness.

After taking probenecid, patients' urine volume dropped by about 30% on average, and they went from waking up several times a night to urinate to about once per night. Many also reported improved quality of life.

"The goal is to preserve the therapeutic benefit of tolvaptan while reducing its burden," Dr. Chebib says.

Despite these promising results, researchers are not planning to rely on probenecid as a long-term solution. The drug is decades old, affects multiple systems in the body and is not widely available today. Instead, the team is using what they learned to design more targeted therapies.

"Probenecid helped us uncover the mechanism," Dr. Chebib says. "Our goal is to take this insight and develop therapies designed specifically for this pathway."

For Dr. Chebib, the work is rooted in early inspiration. He was drawn to kidney research after his father developed PKD.

"This has been a long and deeply purposeful journey," he says. "It started with a personal motivation and led to something that could ultimately benefit patients."

For a complete list of authors, disclosures and funding, see the study.

JOURNALISTS: Soundbites with Dr. Chebib are available in the downloads below.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Sharon Theimer, Mayo Clinic Communications, newsbureau@mayo.edu

The post Researchers identify new kidney pathway with help from 1940s-era drug, may improve polycystic kidney disease treatment (VIDEO) appeared first on Mayo Clinic News Network.

Mayo Clinic is helping shape a new model for delivering hospital-level care beyond traditional settings through an initiative that brings advanced, high-quality care directly to patients in rural and underserved communities. The project is part of a larger federal effort known as the ARPA-H (Advanced Research Projects Agency for Health) PARADIGM (Platform Accelerating Rural Access to Distributed and Integrated Medical Care) program.

Mayo Clinic is a subawardee on the Platform fOr mEdical inTeroperability (POET) project within the PARADIGM program, collaborating with SRI International and the University of Florida to develop intelligent task-guidance systems that help healthcare workers safely perform specific clinical procedures and use medical devices without requiring direct support from specialists.

Mayo's goal is simple but transformative: make it possible for patients to receive reliable, high-quality care closer to home. To do so, Mayo is developing artificial intelligence (AI)-powered tools that support clinicians in safely performing procedures and using medical technologies in environments where specialized care may not always be possible.

Bringing phlebotomy services closer to patients in rural communities

Today, many patients in rural communities who need routine phlebotomy services, such as a blood draw or an IV, may need to travel long distances to access care. With funding from the ARPA-H PARADIGM program, Mayo Clinic is helping enable a model where mobile care teams can deliver these services closer to home.

In the future, a healthcare worker in a mobile care unit could perform a blood draw guided in real time by AI-assisted tools trained on expert technique. Using advanced imaging and computer vision, the system identifies the optimal vein and visually highlights where to place the needle, while also providing step-by-step guidance, similar to a checklist, through each part of the procedure.

During the first year of the program, Mayo recorded 300 blood draws and then used advanced imaging technologies to train AI systems to support tasks like vein selection and technique. "If you think broadly across medical procedures, phlebotomy is arguably the most frequently performed," says W. David Freeman, M.D., professor of neurology and neurosurgery at Mayo Clinic Florida and co-lead on the project. "It's foundational — you need blood draws for diagnostics and IV access for treatment."

Expanding AI-supported procedures to improve access

Similar tools are being developed to reduce delays and expand access to more procedures via guidance at the point of care, including orthopedic splinting.

"This is extremely patient‑centered," says Leslie Simon, D.O., chair of Emergency Medicine at Mayo Clinic Florida, fellowship director of Medical Simulation and co-lead on the project. "If you're going to learn, you learn from the best. The goal is to scale expert knowledge so clinicians in rural or remote areas can perform these procedures with greater confidence and consistency."

By combining clinical expertise with emerging technologies funded through the ARPA-H PARADIGM program, Mayo Clinic is helping develop new models of care that bring services closer to the nearly 1 in 5 Americans living in rural communities, expanding access to timely, high-quality care.

This research was funded, in part, by the U.S. Government. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.

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PHOENIX — Endometriosis and uterine fibroids are two of the most common gynecological conditions. While they have important differences, they also have things in common. Both can lead to serious complications, affect fertility and have symptoms related to the menstrual cycle. And both are the focus of medical innovations to give women better treatment options, explains Megan Wasson, D.O., a gynecologist and chair of gynecology at Mayo Clinic in Arizona.

 "They're both relatively common," Dr. Wasson says. "There can be some overlapping symptoms, but the majority of symptoms vary and the diseases progress differently. Fibroids and endometriosis can run in families. Neither condition is preventable."

Fibroids

Fibroids grow in the uterus. They are almost always noncancerous. You can have one or more. A fibroid may be too small to see with the eyes alone or it can grow as big as a grapefruit or larger, even filling the pelvis or stomach area and making someone appear pregnant.

"These are not just little inconveniences. These are very large, very significant masses and they can really impact quality of life," Dr. Wasson says.

Many people do not experience symptoms and only learn they have fibroids due to a pelvic exam or ultrasound. Others may have symptoms such as heavy, painful, longer or more frequent periods; pain in the pelvis, stomach area or lower back; frequent or difficult urination; constipation; or pain during sex.

"When fibroids become very enlarged, you can actually feel them through the abdominal wall. You can get to the point that your pants do not fit, you have significant abdominal bloating, and the fibroids are pushing on other organs such as the bladder, causing you to have to go to the bathroom all the time, among other symptoms," Dr. Wasson explains. "You can have constipation because the fibroids are pushing on the bowel and not allowing things to move."

In the past, women whose fibroids were problematic were commonly told that a hysterectomy — surgery that removes the uterus, also ending the ability to become pregnant — was the only treatment option.

Now, medical advances are minimizing the impact of fibroid removal surgery on patients, often preserving the uterus and fertility, Dr. Wasson says. Other fibroid treatment options include medications that shrink fibroids and procedures that do not require surgery, she adds.

For example, interventional radiologists can perform a uterine fibroid embolization to block the blood supply to fibroids, causing them to shrink. Patients can usually leave the same day. Reducing the size and alleviating symptoms can help significantly, Dr. Wasson explains.

Other minimally invasive procedures include radiofrequency ablation, which uses energy to cause fibroids to die. Minimally invasive surgeries include a robotic or laparoscopic myomectomy, a surgery to remove the fibroids and leave the uterus in place.

Endometriosis

In endometriosis, tissue similar to the inner lining of the uterus grows outside the uterus. Common symptoms are pelvic pain and cramping, including during menstruation; heavy periods or bleeding between periods; and pain during sex, bowel movements or urination. Sometimes people with endometriosis do not have symptoms and only learn they have it when they have difficulty becoming pregnant or they have surgery for another reason.

"Endometriosis symptoms usually start much earlier in life than fibroids," Dr. Wasson says. "Endometriosis increases the risk for ovarian cancer. It can also cause infertility."

Treatment for endometriosis often involves medication or surgery. Conservative surgery removes endometriosis tissue while aiming to preserve the uterus and ovaries and protect fertility. This surgery may be minimally invasive, using a laparoscope and a small cut. Sometimes a laparoscopic surgery is done with help from robotic devices.

Dr. Wasson is working with a Mayo research team to create a vaccine to prevent endometriosis. She and Mayo colleagues are also exploring ways to make endometriosis easier to detect with medical imaging. Potentially, a molecule could be given during imaging that causes endometriosis to light up, making it easy to see endometriosis tissue, Dr. Wasson explains.

To help detect endometriosis or fibroids as early as possible, Dr. Wasson recommends that, from the time  menstrual cycles start, girls and women pay attention to any irregularities, such as unusually heavy periods, abnormally long or short cycles, missing periods, or symptoms such as pain with periods.

"Your period should be no more than a minor inconvenience," she adds. "If you're missing work, school and other activities, if you're staying in bed because you're having your period, that's not normal. If there are any symptoms causing you to change anything in your life, that warrants a conversation with your healthcare professional. Don't assume a change is normal or is just something you should deal with."

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Sharon Theimer, Mayo Clinic Communications, newsbureau@mayo.edu

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ROCHESTER, Minn. — Mayo Clinic researchers and collaborators have shown that an artificial intelligence (AI) tool can analyze routine pathology slides to help clinicians classify meningiomas, the most common primary brain tumor in adults, and better understand a patient’s risk of tumor recurrence.

The study, published in The Lancet Digital Health, demonstrates that deep learning models can support the extraction of molecular and prognostic information from standard hematoxylin and eosin, or H&E, slides — the same type of tissue images already used in routine clinical care. These insights are typically obtained through DNA methylation profiling, an advanced genetic test which provides valuable diagnostic and prognostic information but can be costly, time-consuming and is unavailable in many hospitals.

"This is one of the many studies where we can harness the strength of digital pathology by capturing the last two decades of genomic and molecular knowledge into AI algorithms," says Gelareh Zadeh, M.D., Ph.D., chair of the Department of Neurologic Surgery at Mayo Clinic in Rochester and the David C. and Flora C. Pratt Distinguished Chief Medical Officer for Mayo Clinic Platform.

Making advanced tumor insights more accessible

Meningiomas can vary widely in behavior. Some grow slowly and may never return after treatment, while others are more aggressive and more likely to recur. Understanding that risk is critical for patients and care teams deciding whether additional treatment, such as radiation therapy, may be needed after surgery.

Molecular testing can help identify which tumors are more likely to recur and which may respond differently to treatment. But these tests require specialized technology and expertise, limiting access for many patients.

Using tissue samples, pathology images and clinical data from 672 patients, researchers developed and tested AI models designed to help identify patterns linked to a tumor's biology. Drawing on multiple de-identified datasets, including data resources from Mayo Clinic Platform, the models supported classification of meningioma subtypes and recurrence risk prediction using standard pathology slides that are already part of routine patient care.

The findings suggest that, with further validation, AI-based tools could one day help clinicians obtain more detailed tumor information to inform patient care, without requiring every patient to undergo advanced genetic testing.

Helping guide treatment decisions

For patients with meningiomas, recurrence risk can influence follow-up care, imaging frequency and whether radiation therapy should be considered. The study found that AI-based predictions remained useful even after accounting for traditional clinical factors such as tumor grade, the extent to which surgery was able to remove the tumor and patient age.

Researchers also found that the AI models could identify patterns of tumor heterogeneity — differences within the same tumor — that may help explain why some tumors behave more aggressively or respond differently to treatment.

The researchers note that additional prospective studies are needed before the AI models can be used routinely in clinical care. Still, they say the findings lay the groundwork for more accessible, personalized care for patients with meningiomas — and potentially for similar AI approaches in other cancers.

As with any clinical decision-support tool, the researchers emphasize that these models would require rigorous evaluation, validation and ongoing physician oversight before being considered for routine care. "The aim is to make these algorithms readily and simply accessible for use globally, improving patient care across many healthcare settings," says Dr. Zadeh.

For a complete list of authors, disclosures and funding, review the publication.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Mayo Clinic Platform
Founded on Mayo Clinic's dedication to patient-centered care, Mayo Clinic Platform enables new knowledge, new solutions, and new technologies through collaborations with health technology innovators to create a healthier world. To learn more, visit Mayo Clinic Platform at www.mayoclinicplatform.org.

Media contact:

• Tia Ford, Mayo Clinic Communications, newsbureau@mayo.edu

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Collaboration aims to expand access to Mayo Clinic’s trusted healthcare expertise and improve patient and clinician experiences

ROCHESTER, Minn., and REDMOND, Wash. — Mayo Clinic and Microsoft today announced a strategic collaboration to develop and deploy a frontier AI model designed specifically for healthcare, making Mayo Clinic’s knowledge, expertise and integrated model of care available to more people when and where they need it. 

The collaboration combines Mayo Clinic’s global healthcare expertise, de-identified clinical health data and longitudinal insights with Microsoft’s advanced AI, cloud, engineering and superintelligence capabilities. Together, the organizations are developing a frontier AI model capable of supporting the broadest scope of clinical reasoning and healthcare use cases.

The model is designed to synthesize diverse clinical data to support earlier diagnoses, more personalized treatment decisions and better patient outcomes. By expanding access to actionable insights and supporting care teams in complex decision-making, the collaboration aims to address some of healthcare’s most challenging problems.

The frontier AI model will be owned by Mayo Clinic, reinforcing Mayo’s long-standing commitment to patient trust, clinical rigor, safety and responsible stewardship of clinical data and AI. Microsoft plans to make the model available through Azure Foundry APIs, enabling organizations worldwide to access advanced healthcare AI capabilities designed to better support patients, clinicians and consumers.

“Mayo Clinic is committed to putting patients first, and we have long believed AI can help transform healthcare. Seven years ago, we launched Mayo Clinic Platform to move healthcare from a pipeline to a platform model through a safe, trusted, patient-centric de-identified data foundation designed to accelerate innovation, breakthroughs, and cures,” said Gianrico Farrugia, M.D., president and CEO, Mayo Clinic. “Now, by combining our clinical expertise and data foundation with Microsoft’s engineering and AI capabilities, we are once again building something new in healthcare and bringing more of Mayo Clinic to more patients.”

Unlike general-purpose AI models, healthcare AI requires deep clinical context, longitudinal understanding, rigorous governance, and real-world validation. The model is being purpose-built for healthcare and initially deployed within Mayo Clinic’s trusted clinical environment, where it can be continuously tested, refined and improved through real-world use.

Mustafa Suleyman, CEO of Microsoft AI, said, “Frontier medical intelligence is around the corner. This is the best collaboration imaginable to help us accelerate towards that future. Mayo has unparalleled clinical expertise, de-identified clinical health data and longitudinal medical insights, and we're thrilled to partner with their world class physicians to build a state-of-the-art foundation model for healthcare.”

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About Mayo Clinic 
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Microsoft
Microsoft (Nasdaq “MSFT” @microsoft) creates platforms and tools powered by AI to deliver innovative solutions that meet the evolving needs of our customers. The technology company is committed to making AI available broadly and doing so responsibly, with a mission to empower every person and every organization on the planet to achieve more.

Media contacts:

• Andrea Kalmanovitz, Mayo Clinic Communications, newsbureau@mayo.edu
• We.Communications for Microsoft, 425-638-7777, rapidresponse@wecommunications.com

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New investments and data scale aim to transform pathology workflows and diagnostic speed

ROCHESTER, Minn. — Mayo Clinic Digital Pathology (MCDP) is advancing efforts to build an integrated innovation ecosystem that supports the future of pathology across clinical care and research. The work reflects Mayo Clinic’s broader digital pathology strategy, including investments in emerging companies, expanded use of digitized pathology data and collaborations designed to improve diagnostic workflows and speed.

As part of this effort, MCDP is collaborating with companies, including Conflux and ViewsML, whose technologies align with its goal of enabling more efficient, scalable and data-informed pathology practices. The initiative is also focused on creating the infrastructure and relationships needed to translate digital pathology innovation into real-world clinical and research impact.

The move reflects growing momentum in the adoption of digital pathology across health systems, as providers seek to address workforce constraints, rising case complexity and demand for faster, more precise diagnoses.

“This commitment reflects Mayo Clinic’s mission to thoughtfully integrate emerging technologies in ways that meaningfully improve patient care,” said Jim Rogers, CEO of Mayo Clinic Digital Pathology. “By advancing digital pathology capabilities, we are enabling our clinicians to deliver faster, more precise insights while also creating new opportunities for research and discovery.”

MCDP is focused on scaling technologies that improve diagnostic accuracy, increase efficiency and support new models of care. Current areas of development and evaluation include AI tools that enhance routine image analysis, improve case-to-slide matching accuracy and reduce reliance on time- and resource-intensive manual processes. Pathologists and clinicians remain responsible for interpreting results and making all clinical decisions related to patient care.

These efforts are part of a broader shift toward software-driven diagnostics and precision medicine, where digital infrastructure and machine learning increasingly play a role in clinical decision-making. While the technologies are still undergoing validation, Mayo Clinic officials say they have the potential to expand access to specialized expertise, accelerate discovery and support more informed treatment decisions.

MCDP’s strategy is anchored by significant internal assets, including a repository of more than 17 million digitized pathology slides and advanced computing capabilities such as the Assisi Cluster. The initiative also connects with Mayo Clinic Laboratories’ global network of more than 3,100 clients across 55+ countries and the Mayo Clinic Platform, which provides data and analytics infrastructure for innovation.

By combining investment, data scale and clinical expertise, Mayo Clinic Digital Pathology aims to position digital pathology as a foundational component of future diagnostics, both within its own system and across the broader healthcare ecosystem.

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About Mayo Clinic Digital Pathology
Mayo Clinic Digital Pathology advances the global adoption of digital pathology to improve patient care and accelerate medical breakthroughs. It supports innovation in slide digitization, data infrastructure, artificial intelligence and diagnostic tool development, working with internal experts and external partners to build and scale new technologies.

About Mayo Clinic  
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Tom Millikin, Mayo Clinic Communications, newsbureau@mayo.org

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New AI-powered solution built on Bayesian's clinical intelligence platform expands access to palliative care, identifies unmet patient needs earlier and reduces readmissions

ROCHESTER, Minn. and NEW YORK — Mayo Clinic and Bayesian Health today announced they have co-developed an artificial intelligence (AI) solution to identify hospitalized patients who may benefit from palliative care earlier in their stay. The solution is designed to support timely consultations, with the objective of improving goal-concordant care for patients with serious illness and reducing non-beneficial readmissions.

Roughly one-third of readmissions involve patients with serious illness, many of whom experience repeated hospitalizations. However, fewer than half of these patients receive palliative care consultations.

To address this challenge, Mayo Clinic and Bayesian Health built a solution that identifies patients with unmet palliative care needs earlier and equips clinicians with the context they need, within their workflow, to navigate the complex conversations and care coordination that follows.

In a randomized clinical trial conducted at Mayo Clinic, validated findings from an earlier version of the program demonstrated that use of the tool was associated with a 44% increase in timely palliative care referrals, a 25% reduction in 60-day readmissions and a 28% reduction in 90-day readmissions, along with improved patient quality of life.

"The challenge in palliative care is not just identifying unmet needs but doing so early enough to change the course of care," said Jacob J. Strand, M.D., chair of Palliative Care at Mayo Clinic. "What makes the difference is tailoring workflows to local culture, based on patient acuity, and across central and bedside teams across the organization. When high-quality, patient-specific signals reach frontline clinicians in the moments that matter, it cuts through the complexity of inpatient care, drives more consistent decision-making and supports teams in delivering the best possible care to every patient."

Mayo Clinic’s Department of Medicine led the clinical development and validation of the AI solution. Bayesian Health supported integration of the model into the electronic health record, allowing care teams to access this information within existing clinical workflows.

This is the first collaboration of its kind at Mayo Clinic to use AI across the entire care process in a complex hospital setting, helping its care teams spot unmet needs earlier, connecting the patient with the right specialists at the right time, while keeping the patient’s health information coordinated but confidential for an overall improvement in care.

How it works

As health systems build out their AI strategies, Bayesian Health provides a clinical foundation of real-time clinical intelligence that shifts care from reactive to proactive. The newest module on the Bayesian platform brings this approach to palliative care, identifying unmet needs such as pain or caregiver support so clinicians can reach patients earlier in their care journey. Palliative care teams get a real-time, hospital-wide view of patients who may benefit from a consult, while bedside clinicians get clear, interpretable guidance and a streamlined path to action, so the moment of insight becomes a moment of care rather than another notification. The clinical AI continuously learns from clinician feedback and local patient populations, improving identification accuracy over time.

"Palliative care is exactly the kind of problem our platform is built for: reaching patients earlier, when clinicians still have time to change the course of their care," said Suchi Saria, Ph.D., founder and CEO of Bayesian Health. "It takes purpose-built infrastructure, rigorous validation and a thoughtful partnership between AI and clinical experts. That's how trustworthy AI gets built, and it's how care actually improves for both patients and caregivers."

This co-development agreement is a strategic collaboration under Mayo Clinic's Practice Transformation Ventures (PTV) framework which includes, but is not limited to, a licensing or vendor arrangement. The Department of Medicine in Rochester served as the Practice owner, providing leadership, clinical expertise and support throughout the project. Data scientists from Mayo Clinic’s Kern Center for Health Care Delivery, in close partnership with clinical teams, helped develop and evaluate the model to support better patient care, reflecting what’s possible when clinical expertise and data science come together to solve real-world problems. 

Mayo Clinic has a financial interest in the technology referenced in this news release. Mayo Clinic will use any revenue it receives to support its not-for-profit mission in patient care, education and research. 

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About Mayo Clinic  
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Bayesian Health
Bayesian Health is the real-time clinical intelligence platform that helps health systems deliver proactive, high-reliability care. By continuously reading the full patient record to establish each patient's baseline and detect meaningful change over time, Bayesian applies complex clinical reasoning to identify the patients who truly need attention and surface clear next steps inside the EHR — turning data noise into trusted, decisive action. Leading health systems partner with Bayesian to make the long-promised shift from reactive to proactive care across key drivers of mortality, readmissions, and length of stay, hardwiring quality as a durable strategy rather than a series of disconnected initiatives. Learn more at https://bayesianhealth.com.

Media contacts:

• Tom Millikin, Mayo Clinic Communications, newsbureau@mayo.edu
• Lauren Levinsky, Bayesian Health, lauren.levinsky@bayesianhealth.com

The post Mayo Clinic and Bayesian Health co-develop new AI-powered solution to expand palliative care access and improve patient outcomes appeared first on Mayo Clinic News Network.