Emery Brown wins a share of 2022 Gruber Neuroscience Prize
Brown and three other scientists recognized for advancing statistical, theoretical analyses of neuroscience data.
Brown and three other scientists recognized for advancing statistical, theoretical analyses of neuroscience data.
Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.
Following the successful development of vaccines against Covid-19, scientists hope to deploy mRNA-based therapies to combat many other diseases.
Innovative brain-wide mapping study shows that an “engram,” the ensemble of neurons encoding a memory, is widely distributed and includes regions not previously realized.
Faculty members recognized for excellence via a diverse array of honors, grants, and prizes.
Competitive seed grants launch yearlong investigations of novel hypotheses about potential causes, biomarkers, treatments of Alzheimer’s and ALS.
Study finds genome loops don’t last long in cells; theories of how loops control gene expression may need to be revised.
The NCSOFT-sponsored program will advance cutting-edge technologies for gaming and data visualization.
Microbes that safely break down antibiotics could prevent opportunistic infections and reduce antibiotic resistance.
AIMBE's highest honor recognizes MIT professor's contributions to neural signal processing, anesthesiology advances.
Professor describes a new research center he is working to develop where researchers will seek to improve patient care by integrating neuroscience and anesthesiology.
A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.
A new deep-learning algorithm trained to optimize doses of propofol to maintain unconsciousness during general anesthesia could augment patient monitoring.
In stepping down as co-director of the Harvard-MIT Program in Health Sciences and Technology, Brown will work to develop a new center for anesthesiology research.
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.