Most antibiotics target metabolically active bacteria, but with artificial intelligence, researchers can efficiently screen compounds that are lethal to dormant microbes.
An interdisciplinary team of researchers thinks health AI could benefit from some of the aviation industry’s long history of hard-won lessons that have created one of the safest activities today.
These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.
A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.
BioAutoMATED, an open-source, automated machine-learning platform, aims to help democratize artificial intelligence for research labs.
The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.
Leo Anthony Celi invites industry to broaden its focus in gathering and analyzing clinical data for every population.
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
