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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 

Data-driven approaches for understanding biology

AI-informed treatment personalization and care management

Privacy preserving, interpretable machine learning algorithms

Recent News
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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...

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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...

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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.


Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study



Personalized predictions of patient outcomes during and after hospitalization using artificial intelligence



Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography



Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes

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