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The MIT Jameel Clinic hosted a daylong closed event for faculty, regulators, and industry experts to discuss what's needed to regulate AI in health.

MIT researchers built DiffDock, a diffusion generative model that could potentially find new drugs faster than traditional methods and reduce the potential for adverse side effects.

MIT-Takeda Program heads into its fourth year with 10 new projects leveraging MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.

MIT researchers developed a geometric deep learning model that is more accurate and over 1,000 times faster at finding potential drug-like molecules than the fastest state-of-the-art computational models, reducing the chances and costs of failures in an industry where 90 percent of drug candidates fail clinical trials.

MIT Professor Rosalind Picard and MGH clinical psychologist Paola Pedrelli are using machine learning and wearable sensors to detect major depressive disorder symptoms in patients.