MEDICAL EXPRESS - HEALTH INFORMATICS

1. Health assessment tool gauges body's biological age better than current methods

   A novel health-assessment tool uses eight metrics derived from a person's physical exam and routine lab tests to characterize biological age. It may be able to predict a person's risk of disability and death better than current health predictors.

2. Addressing health care provider burnout through digital twin systems

   Taylan Topcu is leading a team of Virginia Tech researchers using digital twins to help take better care of health care providers.

3. Findings support use of personalized medicine approach to treat soft tissue sarcomas

   A recent study has demonstrated that a precision medicine approach improves treatment selection for patients with soft tissue sarcomas (STS) in a clinical setting. Published in npj Precision Oncology in March 2025, the research findings support using data-driven and phenotypic screening approaches to treat STS. The study was conducted by researchers from the Agency for Science, Technology and Research (A*STAR), National Cancer Centre Singapore (NCCS) and National University of Singapore (NUS), in collaboration with biotech company, KYAN Technologies.

4. Assessing systemic sclerosis with AI deep neural networks

   Artificial intelligence (AI) is shaping the future of health care, offering new tools for earlier diagnosis of disease and more precise tracking of treatment outcomes. In a new Yale-led study, published in Arthritis Research & Therapy, researchers used a type of AI technology called deep neural network (DNN) analysis to decipher skin involvement and treatment response in patients with systemic sclerosis.

5. US researchers seek to legitimize AI mental health care

   Researchers at Dartmouth College believe artificial intelligence can deliver reliable psychotherapy, distinguishing their work from the unproven and sometimes dubious mental health apps flooding today's market.

6. Ambient AI technology can reduce documentation burden for health care providers

   Researchers at Sutter Health, led by Cheryl Stults, Ph.D., found that an innovative ambient artificial intelligence platform showed promising results in easing the burden of clinical documentation for health care providers. The study, published today in JAMA Network Open, revealed significant reductions in documentation time and improved overall clinician satisfaction. It also highlights the technology's potential to address long-standing challenges in the medical profession.

7. Estimated 7.2 million Americans 65 years and older have Alzheimer's dementia

   An estimated 7.2 million Americans aged 65 years and older are living with Alzheimer's dementia, and almost all adults feel it is important to diagnose the disease in the early stages, according to a report published by the Alzheimer's Association.

8. Researchers develop explainable AI toolkit to predict disease before symptoms appear

   Researchers at the University of Utah's Department of Psychiatry and Huntsman Mental Health Institute have published a paper in Patterns introducing RiskPath, an open-source software toolkit that uses explainable artificial intelligence (XAI) to predict whether individuals will develop progressive and chronic diseases years before symptoms appear, potentially transforming how preventive health care is delivered.

9. AI successfully identifies risk factors linked to more severe pain after knee replacement

   A study using artificial intelligence to classify patient pain archetypes and identify risk for severe pain after knee replacement has earned a Best of Meeting award at the 50th Annual Meeting of the American Society of Regional Anesthesia and Pain Medicine (ASRA). The honor, which recognizes excellence in scientific research, is awarded to three of the top 10 highest-scoring abstracts chosen by the ASRA Research Committee.

10. Making AI models more trustworthy for high-stakes contexts, like classifying diseases in medical images

    The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance, in a chest X-ray, pleural effusion, an abnormal buildup of fluid in the lungs, can look very much like pulmonary infiltrates, which are accumulations of pus or blood.

11. AI chatbots can help pregnant women with opioid use disorder, study finds

    For expectant mothers struggling with opioid use disorder, the stigma surrounding addiction can make it difficult to seek help.

12. Medicine's over-generalization problem—and how AI might make things worse

    In medicine, there's a well-known maxim: never say more than your data allows. It's one of the first lessons learned by clinicians and researchers.

13. AI uncovers hidden patterns in genes that shape disease vulnerability

    Artificial intelligence (AI)-powered protein models combined with genome sequencing technology could help scientists better diagnose and treat genetic diseases, according to new research from The Australian National University (ANU).

14. Roughly half of all women may need extra screening for breast cancer: Some struggle to access it

    When Dr. Shoshana Hallowell, a breast surgeon with McLaren Health System in Lapeer, Michigan, was diagnosed with breast cancer in 2020. She knew it put all of her first-degree relatives at higher risk of developing the same condition.

15. What's that rash? Put some thought into asking Google for medical help

    Dr. Google is often on call for worried patients, but it may not give the best advice.

16. AI is giving a boost to efforts to monitor health via radar

    If you wanted to check someone's pulse from across the room, for example to remotely monitor an elderly relative, how could you do it? You might think it's impossible, because common health-monitoring devices such as fingertip pulse oximeters and smartwatches have to be in contact with the body.

17. AI tools can make education materials more patient friendly

    Artificial intelligence (AI) tools significantly improve the readability of online patient education materials (PEMs), making them more accessible, a new study shows.

18. Greater share of US losing faith in health guidance, poll says

    About 44% of U.S. adults say they expect to lose trust in government health recommendations over the next four years because of federal leadership changes, according to a poll published April 29 by Harvard University and the de Beaumont Foundation.

19. Most Americans want easy early testing for Alzheimer's, survey reveals

    Most Americans want to know if they're destined to lose their brain power to Alzheimer's disease, according to an annual report produced by the Alzheimer's Association.

20. App helps asthma patients track symptoms

    A smartphone app can help asthma patients better track their symptoms and live healthier, a new study says.

21. AI-driven analysis of digital pathology images may improve pediatric sarcoma subtyping

    An artificial intelligence (AI)-based model accurately classified pediatric sarcomas using digital pathology images alone, according to results presented at the American Association for Cancer Research (AACR) Annual Meeting, held April 25–30.

22. AI-ECG aids early heart issue detection in women

    Every year, some mothers die after giving birth due to heart problems, and many of these deaths could be prevented. The ability to screen for heart weakness before pregnancy could play a crucial role in identifying women who may need additional care to improve pregnancy outcomes. Mayo Clinic researchers, led by Anja Kinaszczuk, D.O., and Demilade Adedinsewo, M.D., tested artificial intelligence (AI) tools, using recordings from an electrocardiogram (ECG) and a digital stethoscope, to find unknown heart problems in women of childbearing age seen in primary care.

23. AI technique can uncover antiviral compounds using limited data

    Artificial intelligence algorithms have now been combined with traditional laboratory methods to uncover promising drug leads against human enterovirus 71 (EV71), the pathogen behind most cases of hand, foot and mouth disease.

24. Study lauds Indiana's data-driven approach to population health

    A study by Assistant Professor Karmen S. Williams and colleagues highlights Indiana's health data network as a model for the nation.

25. Bridging the AI gap in medicine: New framework targets family doctor education

    A team of Canadian researchers has developed a curriculum framework to help train future family physicians in the use of artificial intelligence (AI), addressing a critical gap in medical training as digital tools become more common in patient care.

26. Platform technology screens millions of drugs and genes to reveal new therapeutic pathways

    Researchers from the University of Adelaide have developed a new technology for drug and functional genomics screenings, which could reshape the way diseases are treated.

27. A new computational framework illuminates the hidden ecology of diseased tissues

    To understand what drives disease progression in tissues, scientists need more than just a snapshot of cells in isolation—they need to see where the cells are, how they interact, and how that spatial organization shifts across disease states. A computational method called MESA (Multiomics and Ecological Spatial Analysis), detailed in a study published in Nature Genetics, is helping researchers study diseased tissues in more meaningful ways.

28. Trouble hearing in noisy places and crowded spaces? A new algorithm could help hearing aid users

    When a group of friends gets together at a bar or gathers for an intimate dinner, conversations can quickly multiply and mix, with different groups and pairings chatting over and across one another.

29. Making AI speak the doctor's language: AI tool interprets ECG images with pixel-level precision

    The electrocardiogram (ECG) is one of the most essential tools in modern medicine, used to detect heart problems ranging from arrhythmias to structural abnormalities. In the U.S. alone, millions of ECGs are performed each year, whether in emergency rooms or routine doctor visits. As artificial intelligence (AI) systems become more advanced, they are increasingly being used to analyze ECGs—sometimes even detecting conditions that doctors might miss.

30. AI analyzes patient data to detect multiple sclerosis progression, improving early treatment decisions

    To provide the right treatment for multiple sclerosis (MS), it is important to know when the disease changes from relapsing-remitting to secondary progressive, a transition that is currently recognized on average three years too late. Researchers at Uppsala University have now developed an AI model that can determine with 90% certainty which variant the patient has. The model increases the chances of starting the right treatment in time and thus slowing the progression of the disease.