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Machine Learning for Informed Sequential Clinical Decision Making


Term:

Summer

Department:

QI: MIT Quest for Intelligence

Faculty Supervisor:

Li-wei Lehman

Faculty email:

lilehman@mit.edu

Apply by:

8/1/2020

Contact:

Li-wei Lehman: lilehman@mit.edu

Project Description

We are seeking highly-motivated students to participate in research to apply/develop machine learning approaches for informed sequential clinical treatment decision making. The project involves developing an AI tool based on causal inference methods to facilitate treatment decision making for ICU patients. This project will combine machine learning and causal inference techniques for counterfactual outcome predictions under time-varying treatments using both simulated data and longitudinal (time-series) data from electronic health records. Relevant URLs: https://arxiv.org/abs/2003.10551 http://web.mit.edu/lilehman/www/

Pre-requisites

Knowledge and experience in machine learning (or statistics) strongly preferred. Experience in one or more of the following areas would be desirable: deep learning, representation learning, longitudinal data analysis, or causal inference.