MEDICAL EXPRESS - HEALTH INFORMATICS

1. Machine learning uncovers social risk clusters linked to suicide across the US

   Using machine learning technology, a new study has identified three distinct profiles describing social and economic factors that are associated with a higher risk of suicide. Scientists at Weill Cornell Medicine and Columbia University Vagelos College of Physicians and Surgeons led the research that showed suicide rates vary significantly across the three clusters and that the patterns differ geographically across the United States.

2. AI tool accurately sorts cancer patients by their likely outcomes

   A new artificial intelligence-based method accurately sorts cancer patients into groups that have similar characteristics before treatment and similar outcomes after treatment, according to a study led by investigators at Weill Cornell Medicine. The new approach has the potential to enable better patient selection in clinical trials and better treatment selection for individual patients.

3. Study explores AI's ability to improve differential diagnosis accuracy

   The development of more accessible artificial intelligence (AI) models has transformed the field of health diagnoses and medicine, with AI being used for diagnostic accuracy, personalized treatment plans, interpreting medical images, streamlining operations, supporting remote patient monitoring and much more.

4. Spit science: Why saliva is a great way to detect disease

   A few drops of saliva can now reveal what used to require a scalpel, a syringe or a scan.

5. COVID-19 tests, other health supplies provided free at 51 kiosks across LA County

   Starting this week, residents in need of a COVID-19 self-test kit, fentanyl test strips or other health supplies can get them for free at any of 51 Community Health Station kiosks across Los Angeles County.

6. AI tool uses selfies to predict biological age and cancer survival

   Doctors often start exams with the so-called "eyeball test"—a snap judgment about whether the patient appears older or younger than their age, which can influence key medical decisions.

7. Machine learning brings consistency to newborn genetic screening

   More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care.

8. Chatbot accuracy: Study evaluates medical advice from AI chatbots and other sources

   A team of AI and medical researchers, affiliated with several institutions in the U.K. and the U.S. has tested the accuracy of medical information and advice given by LLMs to users. In their paper posted on the arXiv preprint server, the group describes how they asked 1,298 volunteers to query chatbots for medical advice. They then compared the results to advice from other online sources or the user's common sense.

9. AI tool uses face photos to estimate biological age and predict cancer outcomes

   Eyes may be the window to the soul, but a person's biological age could be reflected in their facial characteristics. Investigators from Mass General Brigham developed a deep learning algorithm called "FaceAge" that uses a photo of a person's face to predict biological age and survival outcomes for patients with cancer.

10. Blood test for many cancers could thwart progression to late stage in up to half of cases, study suggests

    A single blood test, designed to pick up chemical signals indicative of the presence of many different types of cancer, could potentially thwart progression to advanced disease while the malignancy is still at an early stage and amenable to treatment in up to half of cases, suggests a modeling study published in the open access journal BMJ Open.

11. European controls to mitigate bias in AI health care systems are inadequate, say researchers

    Artificial intelligence systems are being increasingly used in all sectors, including health care. They can be used for different purposes; examples include diagnostic support systems (e.g., a system widely used in dermatology to determine whether a mole could develop into melanoma) or treatment recommendation systems (which, by inserting various parameters, can suggest the type of treatment best suited to the patient).

12. AI model provides clues about how a virus may evolve and the immune response it could provoke

    Effective vaccines dramatically changed the course of the COVID-19 pandemic, preventing illness, reducing disease severity, and saving millions of lives.

13. Why screen for iron deficiency? It's common, consequential and curable

    Iron deficiency—when there's too little iron in the blood—may affect a quarter of the world's population, and in particular, women of reproductive age. Symptoms can include fatigue and shortness of breath, and without treatment, iron deficiency can progress to anemia, a condition characterized by low red blood cell count that can cause more severe heart and health problems.

14. New tool to fast-track ovarian cancer diagnosis

    A woman's chances of surviving ovarian cancer at least five years after diagnosis come down to the toss of a coin: just 49% will reach that milestone, making it one of the most lethal reproductive cancers worldwide.

15. Foot traffic can predict COVID-19 spread in New York City neighborhoods

    A new study published in the journal PLOS Computational Biology reveals how foot traffic data from mobile devices can enhance neighborhood-level COVID-19 forecasts in New York City. The research, led by researchers at Columbia University Mailman School of Public Health and Dalian University of Technology, provides a novel approach to predicting the spread of the SARS-CoV-2 virus and improving targeted public health interventions during future outbreaks.

16. New machine learning tool predicts a child's personal risk for cisplatin-induced hearing loss

    The powerful chemotherapy drug cisplatin has been used since the late 1970s to treat a variety of cancers. It's highly effective against solid tumors and is often a core element of treatment for children with brain and spinal cord tumors, neuroblastoma, and rhabdomyosarcoma.

17. AI-human task-sharing could cut mammography screening costs by up to 30%

    The most effective way to harness the power of artificial intelligence when screening for breast cancer may be through collaboration with human radiologists—not by wholesale replacing them, says new research co-written by a University of Illinois Urbana-Champaign expert in the intersection of health care and technology.

18. Real-time AI-driven decision support aids catheter ablation

    An artificial intelligence (AI)-driven model can significantly improve procedural safety in cardiac electrophysiology with real-time decision support, according to a study presented at the annual meeting of the Heart Rhythm Society, held from April 24 to 27 in San Diego.

19. AI trained on de-identified patient data to predict health care needs in pilot study

    Foresight, a generative AI model, learns to predict what happens next based on previous medical events. It's similar to models like ChatGPT, which predicts the next word in a sentence based on what it's seen previously from data across the internet.

20. AI model improves delirium prediction, leading to better health outcomes for hospitalized patients

    An artificial intelligence (AI) model improved outcomes in hospitalized patients by quadrupling the rate of detection and treatment of delirium. The model identifies patients at high risk for delirium and alerts a specially trained team to assess the patient and create a treatment plan, if needed.

21. New algorithms can help GPs predict which of their patients have undiagnosed cancer

    Two new advanced predictive algorithms use information about a person's health conditions and simple blood tests to accurately predict a patient's chances of having a currently undiagnosed cancer, including hard-to-diagnose liver and oral cancers. The new models could revolutionize how cancer is detected in primary care, and make it easier for patients to get treatment at much earlier stages.

22. AI therapy may help with mental health, but innovation should never outpace ethics

    Mental health services around the world are stretched thinner than ever. Long wait times, barriers to accessing care and rising rates of depression and anxiety have made it harder for people to get timely help.

23. Researchers raise red flag about AI-generated fake images in biomedical research

    The authors of an editorial published in the American Journal of Hematology, claim that "generative Artificial Intelligence can be exploited to produce fraudulent scientific images, either from scratch or by modifying existing visual materials to increase the realism of the final fabricated product."

24. Discovery uses gut bacteria and AI to diagnose a chronic pain syndrome

    McGill University researchers, in collaboration with colleagues in Israel and Ireland, have developed AI technology that can detect patterns in gut bacteria to identify complex regional pain syndrome (CRPS) with remarkable accuracy, potentially transforming how CRPS is diagnosed and treated.

25. How analytics is driving decisions and outcomes in health care

    What if data could help predict a patient's prognosis, streamline hospital operations, or optimize human resources in medicine? A book fresh off the shelves, "The Analytics Edge in Healthcare," shows that this is already happening, and demonstrates how to scale it.

26. New review of performance measures for diabetes finds many measures inadequate

    A review by the American College of Physicians (ACP) of performance measures for diabetes found that of the 14 performance measures relevant to internal medicine, only four meet ACP's rigorous standards for appropriate use, high-quality evidence, and scientific acceptability. "Quality Indicators for Diabetes in Adults: A Review of Performance Measures by the American College of Physicians" was published today in the Annals of Internal Medicine.

27. 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.

28. 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.

29. 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.

30. 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.