Is medicine ready for AI? Doctors, computer scientists, and policymakers are cautiously optimistic
With the artificial intelligence conversation now mainstream, the 2023 MIT-MGB AI Cures conference saw attendance double from previous years.
With the artificial intelligence conversation now mainstream, the 2023 MIT-MGB AI Cures conference saw attendance double from previous years.
MIT researchers built DiffDock, a model that may one day be able to find new drugs faster than traditional methods and reduce the potential for adverse side effects.
Seven researchers, along with 14 additional MIT alumni, are honored for significant contributions to engineering research, practice, and education.
Deep-learning model takes a personalized approach to assessing each patient’s risk of lung cancer based on CT scans.
New fellows are working on health records, robot control, pandemic preparedness, brain injuries, and more.
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
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.