Overview

The “Healthy ML” group at MIT, led by Dr. Marzyeh Ghassemi, focuses on creating and applying machine learning to understand and improve health in ways that are robust, private and fair. Health is important, and improvements in health improve lives. However, we still don’t fundamentally understand what it means to be healthy, and the same patient may receive different treatments across different hospitals or clinicians as new evidence is discovered, or individual illness is interpreted.

Unlike many problems in machine learning - games like Go, self-driving cars, object recognition - disease management does not have well-defined rewards that can be used to learn rules. Models must also be “healthy”, in that they should not learn biased rules or recommendations that harm minorities or minoritized populations. The Healthy ML group tackles the many novel technical opportunities for machine learning in health, and works to make important progress with careful application to this domain.

Read more about our Research Directions and Publications.

News

  • Nov 2023 - New comment paper has published in Nature Human Behaviour on fair use of AI by physicians!
  • We are excited to host the MIT ML+Health Seminar Series this Fall!
  • Aug 2023 - Congratulations to Hyewon, who presented her paper at MLHC 2023!
    • Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals [Paper] [Code]
      Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi
  • Jul 2023 - Congratulations to Vinith and Haoran, who presented their papers at ICML 2023! Also, Marzyeh is giving a keynote speech at ICML 2023!
    • When Personalization Harms: Reconsidering the Use of Group Attributes of Prediction [Paper] [Code]
      Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun
    • Change is Hard: A Closer Look at Subpopulation Shift [Paper] [Code]
      Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi

Joining the Lab

As an MIT undergrad interested in an UROP: Contact Sheila Sharbetian (sheilash@csail.mit.edu) to determine if there are research slots available for the semester, and schedule a 30 minute session with Dr. Ghassemi.

As an MIT MEng: Contact Sheila Sharbetian (sheilash@csail.mit.edu) with a topic and research plan that is relevant to the group.

As an external student: Apply for the MIT EECS or IMES PhD programs, select Marzyeh Ghassemi as a PI you are interested in working with.