Can AI help predict which heart-failure patients will worsen within a year?
Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.
Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.
Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.
Read MoreA new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
Read MoreAssistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.
Read MoreFrom early motion-sensing platforms to environmental monitoring, the professor and head of the Program in Media Arts and Sciences has turned decades of cross-disciplinary research into real-world impact.
Read MoreA new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
Read MoreThe approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.
Read MoreBy leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
Read MoreBy providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
Read MoreResearch from the MIT Center for Constructive Communication finds leading AI models perform worse for users with lower English proficiency, less formal education, and non-US origins.
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