TalkRL: The Reinforcement Learning Podcast

← TalkRL: The Reinforcement Learning Podcast14. Aug. · 1 Std. 27 Min.

Thomas Frost on Clinical RL with Natural Timings

Thomas Frost on Clinical RL with Natural Timings14. Aug.1 Std. 27 Min.

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 References

Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning

Thomas Frost, Kezhi Li, Steve Harris — ML4H Symposium, PMLR 259, 2025

Insulin4RL: 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, 2026

Insulin4RL: Real-Time Insulin Management in the Intensive Care Unit for Offline Reinforcement Learning

Thomas Frost, Steve Harris — arXiv preprint, 2026

Additional References

The 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