Jameel Clinic The Epicenter of AI & Healthcare at MIT


See our new initiative in the fight against COVID-19, AI Cures.

OUR MISSION
Our goal is to develop AI technologies that will change the landscape of healthcare. This includes early diagnostics, drug discovery, care personalization and management. Building on MIT’s pioneering history in artificial intelligence and life sciences, we are working on novel algorithms suitable for modeling biological and clinical data across a range of modalities including imaging, text and genomics. While achieving this goal, we strive to make new discoveries in machine learning, biology, chemistry and clinical sciences. Our other defining trait: emphasis on translating our discoveries into technologies that can improve people’s lives. To realize this mission, we support research and educational activities in the AI/Healthcare space and establish collaborations with hospitals, industry partners and foundations that share our vision.
Machine learning algorithms for analyzing life science and clinical data
Predictive modeling for early diagnostics
In-silico algorithms for
drug discovery
1/7
Data-driven approaches for understanding biology
AI-informed treatment personalization and care management
Privacy preserving, interpretable machine learning algorithms
Recent News

What can your microwave tell you about your health?
An MIT system uses wireless signals to measure in-home appliance usage to better understand health tendencies. For many of us our...

New rapid CRISPR-based test for SARS-CoV-2 detection
A new study reports the approval of a new CRISPR-based coronavirus test that is both sensitive and rapid and intended to help reduce the time...

Jim Collins Receives Funding for AI Drug Discovery
The Audacious Project commitment will support the development of new classes of antibiotics to treat the world’s deadliest bacterial pathogens.
Trending AI & Health Research
Research from around the world. Updated weekly.
01/
Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study
Button
03/
Personalized predictions of patient outcomes during and after hospitalization using artificial intelligence
Button
02/
Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography
Button
04/
Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes
Button