Health Informatics

Mount Sinai researchers developed an AI model to make individualized treatment recommendations for atrial fibrillation (AF) patients—helping clinicians accurately decide whether or not to treat them with anticoagulants (blood thinner medications) to prevent stroke, which is currently the standard treatment course in this patient population. This model presents a completely... Read more

UCLA engineers have developed a wearable, noninvasive brain-computer interface system that utilizes artificial intelligence as a co-pilot to help infer user intent and complete tasks by moving a robotic arm or a computer cursor.... Read more

Collecting high-quality genomic data is time-consuming, expensive, and often only possible through large-scale national efforts. Thankfully, a new tool developed by the UC Santa Cruz Genomics Institute's Computational Genomics Lab is making existing datasets easier to find and use, ensuring that more researchers can build on these precious resources rather... Read more

Measurements with a miniature camera inside the coronary arteries can accurately predict whether someone will suffer a recurrent heart attack. Until now, interpreting these images was so complex that only specialized laboratories could perform it.... Read more

Concerned about the ability of artificial intelligence models trained on data from urban demographics to make the right medical diagnoses for rural populations, West Virginia University computer scientists have developed several AI models that can identify signs of heart failure in patients from Appalachia.... Read more

An AI-enabled stethoscope can help doctors pick up three heart conditions in just 15 seconds, according to the results of a real-world trial presented at the European Society of Cardiology's annual congress in Madrid.... Read more

EPFL researchers have developed a powerful method to generate brain-wide, biologically realistic wiring maps of the mouse brain. Their approach bridges experimental data with mathematical and computational modeling to simulate how neurons connect across the entire brain.... Read more

Machine learning (ML) models predict in-hospital mortality in intensive care unit (ICU) patients with lymphoma, according to a study published online Aug. 20 in PLOS ONE.... Read more

Asystole is the most serious form of cardiac arrest. It happens when the heart stops beating and there is no more electrical activity. It is sometimes called "flat-line" or "flat-lining" because the lines on an electrocardiogram become flat when electrical activity ceases.... Read more

A new ESC/EAS Focused Update to guidelines, about how best to manage lipid levels in patients to reduce cardiovascular risk, recommends the use of new cardiovascular risk prediction algorithms. The update was released at ESC Congress 2025 and published in the European Heart Journal.... Read more

Australian GPs are not adequately monitoring for adverse health outcomes in children and adolescents who are prescribed antipsychotic drugs, according to a new study by University of Adelaide researchers.... Read more

Researchers at Endeavor Health and Northwestern University have created an artificial intelligence-based tool to help doctors recognize an underdiagnosed, often fatal respiratory syndrome found in critically ill hospital patients. The tool has already identified historical cases with 93% accuracy, and it will soon be piloted for patients in treatment at... Read more

When genetic testing reveals a rare DNA mutation, doctors and patients are frequently left in the dark about what it actually means. Now, researchers at the Icahn School of Medicine at Mount Sinai have developed a powerful new way to determine whether a patient with a mutation is likely to... Read more

Every year, global health experts are faced with a high-stakes decision: Which influenza strains should go into the next seasonal vaccine? The choice must be made months in advance, long before flu season even begins, and it can often feel like a race against the clock. If the selected strains... Read more

A new study by researchers at the University of Exeter has found that routine blood tests used in primary care to assess anemia and mean corpuscular volume (MCV) are more effective at predicting cancer risk in white patients than in Asian or Black patients.... Read more