"Hey,Charlie" app supports those struggling with opioids
Smartphone app developed by Emily Lindemer PhD '17 uses social contacts and location information to give gentle reminders for staying engaged with recovery.
Automated system identifies dense tissue, a risk factor for breast cancer, in mammograms
Deep-learning model has been used successfully on patients, may lead to more consistent screening procedures.
Student entrepreneurs think inside the box
Living and working in a glass cube, an interdisciplinary team of students reimagined the ambulance of the future as part of a global startup competition.
Amy Finkelstein, Lisa Parks win 2018 MacArthur Fellowships
Health care economist and media studies scholar are the latest MIT faculty to nab prestigious “genius grant.”
Abdul Latif Jameel Clinic for Machine Learning in Health at MIT aims to revolutionize disease prevention, detection, and treatment
A key part of the MIT Quest for Intelligence, J-Clinic builds on MIT expertise across multiple scientific disciplines.
Model can more naturally detect depression in conversations
Neural network learns speech patterns that predict depression in clinical interviews.
Model improves prediction of mortality risk in ICU patients
By training on patients grouped by health status, neural network can better estimate if patients will die in the hospital.
A "GPS for inside your body"
CSAIL wireless system suggests future where doctors could implant sensors to track tumors or even dispense drugs.
MIT AgeLab partners with Tivity Health for Connectivity Summit on Rural Aging
Attendees address rural social isolation among aging populations in America.
Artificial intelligence model “learns” from patient data to make cancer treatment less toxic
Machine-learning system determines the fewest, smallest doses that could still shrink brain tumors.
Challenge seeks innovations to improve wellbeing in aging populations
MIT AgeLab launches In Good Company global challenge in partnership with GE, Benchmark Senior Living, and the Massachusetts Council to Address Aging.
Three MIT-incubated ventures chosen for first Techstars Impact class
Base Operations, MDaaS Global, and Graviky Labs will head to Texas to be part of the first class at the new elite accelerator.
Automating molecule design to speed up drug development
Machine-learning model could help chemists make molecules with higher potencies, much more quickly.
![“What we discovered is, very little [Medicare] money is spent on people who we know with high probability are going to die in a short amount of time,” says Amy Finkelstein, a professor in MIT’s Department of Economics and co-author of a paper in the journal Science.](/sites/default/files/styles/term_page__news_article/public/images/201806/MIT-Health-Care-Spending.jpg?itok=uM3yQvcx)
The value of late-in-life health care spending
Study debunks notion that large chunks of Medicare go to futile end-of-life care.
Faster analysis of medical images
Algorithm makes the process of comparing 3-D scans up to 1,000 times faster.