12 citations · 14 across the 6 of their papers we have counts for
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cs.LG2020★ 2 cited
Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies
Christina X. Ji, Michael Oberst, Sanjat Kanjilal +1
Reinforcement learning (RL) has the potential to significantly improve clinical decision making. However, treatment policies learned via RL from observational data are sensitive to…
cs.LG2020
Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes
Soorajnath Boominathan, Michael Oberst, Helen Zhou +2
In several medical decision-making problems, such as antibiotic prescription, laboratory testing can provide precise indications for how a patient will respond to different treatme…