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Treatment, evidence, imitation, and chat

arXiv 2506.23040 ↗First posted 29 Jun 2025stat.OT cs.AIcited by 0

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Abstract (arXiv)

Large language models are thought to have the potential to aid in medical decision making. This work investigates the degree to which this might be the case. We start with the treatment problem, the patient's core medical decision-making task, which is solved in collaboration with a clinician. We discuss different approaches to solving it, including, within evidence-based medicine, experimental and observational data. We then discuss the chat problem, and how this differs from the treatment problem -- in particular with respect to imitation (and how imitation alone cannot solve the true treatment problem, although this does not mean it is not useful). We then discuss how a large-language-model-based system might be trained to solve the treatment problem, highlighting that the major challenges relate to the ethics of experimentation and the assumptions associated with observation. We finally discuss how these challenges relate to evidence-based medicine and how this might inform the efforts of the medical research community to solve the treatment problem. Throughout, we illustrate our arguments with the cholesterol medications, statins.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 111 references that are in the map. First posted on arXiv 29 Jun 2025.

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References · 26

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14 more
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