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.
New MIT faculty member investigates how sensory input from within the body controls mammalian physiology and behavior.
Leo Anthony Celi invites industry to broaden its focus in gathering and analyzing clinical data for every population.
The bioderived “smart sutures” could help patients heal after bowel resection or other types of surgery.
The method could enable a rapid test to determine whether individuals are producing antibodies that help protect against Covid-19.
A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.
A campus summit with the leader and his delegation centered around dialogue on biotechnology and innovation ecosystems.
The device, which uses electricity to boost hormone production in the stomach, could help to ease nausea and counteract appetite loss.
The new diagnostic, which is based on analysis of urine samples, could also be designed to reveal whether a tumor has metastasized.
The printer generates vaccine-filled microneedle patches that can be stored long-term at room temperature and applied to the skin.
In a new study, immunostimulatory drugs slowed tumor growth without producing systemic inflammation.
A new analysis reveals how Staphylococcus aureus gains mutations that allow it to colonize eczema patches.
He conducted groundbreaking research into auditory physiology at MIT and Harvard Medical School, and was the founding director of the Eaton-Peabody Laboratories at Mass Eye and Ear.
Senior Victor Damptey brings his Spanish-speaking abilities to bear as he works toward becoming a physician-scientist.
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.