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.
The device senses and wirelessly transmits signals related to pulse, sweat, and ultraviolet exposure, without bulky chips or batteries.
Mathematical modeling speeds up the process of programming bacterial systems to self-assemble into desired 2D shapes.
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.
An anomaly-detection model developed by SMART utilizes machine learning to quickly detect microbial contamination.
Ritu Raman leads the Raman Lab, where she creates adaptive biological materials for applications in medicine and machines.
MIT professor will leverage his research into machine learning and computer science, as well as his role as a practicing cardiologist, toward educating clinician-scientists and engineers.
Rapid and accurate analytical test method enhances the production of high-quality cell therapy products.
MIT neuroscientists expand CRISPR toolkit with new, compact Cas7-11 enzyme.
MIT spinout Frequency Therapeutics’ drug candidate stimulates the growth of hair cells in the inner ear.
Researchers create a mathematical framework to examine the genome and detect signatures of natural selection, deciphering the evolutionary past and future of non-coding DNA.
Life sciences class brings biotech industry experience into the classroom with part-time internships for graduate students.
Novel lysin Abp013 has shown promising antimicrobial ability against Acinetobacter baumannii and Klebsiella pneumoniae.
In the intensity of basic training, a smartwatch-based system warns recruits when they are at risk of heat injury.
HASTS PhD student Rijul Kochhar tracks changing medical and microbial realities, and examines what they portend for society.