A new diagnostic method would confirm sepsis infections earlier, cutting critical hours in the “race against time” to save patients’ lives.

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 actually develop disease, a concept known in genetics as penetrance.

An AI tool could help cardiologists identify and target cells that trigger arrhythmia in patients with ventricular tachycardia, a serious heart condition.

Researchers at Baylor College of Medicine have developed an artificial intelligence (AI) model that reveals how protein modifications link genetic mutations to disease. The method, called DeepMVP and published in Nature Methods, significantly outperforms previously published models and has implications for the development of novel therapeutics.

In the Age of AI, many health care providers dream of a digital assistant, unencumbered by fatigue, workload, burnout or hunger, that could provide a quick second opinion for medical decisions, including diagnoses, treatment plans and prescriptions.