TalkRL: The Reinforcement Learning Podcast

Thomas Frost on Clinical RL with Natural Timings

TalkRL: The Reinforcement Learning Podcast

Show Notes

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. 2018 Off by a beat: the effects of temporal misalignment in reinforcement learning for sepsis treatment — Tang et al. 2026 Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment — Zhang et al. 2021 Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment — Brown et al. 2025 Loss of plasticity in deep continual learning — Dohare et al. 2024

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