EPISODE · Aug 14, 2026 · 1H 27M
Thomas Frost on Clinical RL with Natural Timings
from TalkRL: The Reinforcement Learning Podcast · host Robin Ranjit Singh Chauhan
Dr Thomas Frost is an emergency physician based in London, UK. He is also in the final stages of completing a PhD at University College London, where he has been looking at offline reinforcement learning applied to healthcare settings.Featured ReferencesRobust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning Thomas Frost, Kezhi Li, Steve Harris — ML4H Symposium, PMLR 259, 2025Insulin4RL: Real-Time Insulin Infusions for Offline Reinforcement Learning Thomas Frost, Steve Harris — PhysioNet, 2026 (RRID:SCR_007345)The Hidden Risks of Temporal Resampling in Clinical Reinforcement Learning Thomas Frost, Hrisheekesh Vaidya, Steve Harris — arXiv preprint, 2026Insulin4RL: Real-Time Insulin Management in the Intensive Care Unit for Offline Reinforcement Learning Thomas Frost, Steve Harris — arXiv preprint, 2026Additional ReferencesThe artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care — Komorowski et al. 2018Off by a beat: the effects of temporal misalignment in reinforcement learning for sepsis treatment — Tang et al. 2026Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment — Zhang et al. 2021Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment — Brown et al. 2025Loss of plasticity in deep continual learning — Dohare et al. 2024
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Thomas Frost on Clinical RL with Natural Timings
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