AI for Medicine

Large language models may help psychiatrists resolve unanswered questions about mental illness. Researchers from University College London, Beijing Normal University, and Lisbon’s Champalimaud Centre for the Unknown used a large language model to...

A deep learning system detected breast cancer in mammograms as well as experienced radiologists, according to a landmark study.

Eric Topol is one of the world’s leading advocates for AI in medicine. Below he shares his insights into the fusion of AI and medicine and advice for machine learning engineers who want to get involved.

The wearable revolution is helping doctors figure out what’s troubling your ticker — thanks to deep learning. The problem: Arrhythmias, a range of conditions in which the heart beats too fast, too slow, or erratically, can cause heart attack or stroke.

An AI-driven alarm system helps rescue patients before infections become fatal. The problem: Machine learning can spot patterns in electronic health data indicating where a patient’s condition is headed that may be too subtle for doctors and nurses to catch.

Will deep learning discover new medicines? Startups — and big-pharma partners — are betting on it. The problem: In theory, there’s a pharmacological cure for just about any ailment. In practice, discovering those therapies takes years and billions of dollars.

Doctors are overwhelmed by clerical work. Healthcare-savvy voice assistants are picking up the slack.