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Machine Learning for Informed Sequential Clinical Decision Making
QI: MIT Quest for Intelligence
Li-wei Lehman: email@example.com
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/
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.