Pitt Team receives $9M grant for Parkinson’s research
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Updates every hour. Last Updated: 3-Jun-2026 18:17 ET (3-Jun-2026 22:17 GMT/UTC)
Researchers have developed artificial intelligence (AI) models that can scrutinize electronic health records (EHR) and electrocardiograms to identify individuals in the general population at elevated risk for sudden cardiac arrest — a condition that causes more than 400,000 U.S. deaths annually and has a survival rate of only 10%.
The finding represents a significant advance in predicting a largely unpredictable medical emergency that often strikes people with no known heart disease.
"Using artificial intelligence applications and health records data, the prediction of cardiac arrest in the general population is feasible,” said Dr. Neal Chatterjee, the study’s lead investigator and a cardiologist at the University of Washington School of Medicine.
JACC: Advances, a journal of the American College of Cardiology, published the paper today. Other co-senior authors are from Massachusetts General Hospital and the Broad Institute of MIT and Harvard.
Polycystic ovary syndrome (PCOS), a condition affecting more than 170 million people worldwide, has been officially renamed Polyendocrine Metabolic Ovarian Syndrome (PMOS) following a landmark global consensus study published today in The Lancet.
A new worm model developed by Brown University researchers could play a key role in treating a rare genetic disease that causes paralysis in children and worsens with age. Developed in the lab of neuroscientist Anne Hart, a genetically engineered C. elegans nematode model provides a fast, inexpensive way to evaluate potential drug treatments for alternating hemiplegia of childhood, or AHC, a disorder that currently has no cure or effective treatments.