An MIT-developed device with the appearance of a Wi-Fi router uses a neural network to discern the presence and severity of one of the fastest-growing neurological diseases in the world.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.
The brilliant scientist was known for both the depth of his intellect and his kindness.
Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.
MIT and Mass General Brigham researchers and physicians connect in person to bring AI into mainstream health care.
New fellows are working on electronic health record algorithms, remote sensing data related to environmental health, and neural networks for the development of antibiotics.
The machine-learning model could help scientists speed the development of new medicines.
MIT scientist Rosalind Picard collaborates with clinicians to develop tools for mental health care delivery.
Scientists demonstrate that AI-risk models, paired with AI-designed screening policies, can offer significant and equitable improvements to cancer screening.
Cardiologist Demilade Adedinsewo is using her MIT Professional Education experience to advance cardiovascular care at the Mayo Clinic.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
MIT researchers employ machine learning to find powerful peptides that could improve a gene therapy drug for Duchenne muscular dystrophy.
Nearly 300 government and military members participated in a new course designed to explore the next generation of artificial intelligence and related technologies.
Nearly 1,400 joined the AI for Health Care Equity Conference that explored new AI technologies as a platform for change.