Treatment, evidence, imitation, and chat

Samuel J. Weisenthal
6/29/2025
stat.OTcs.AI

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Abstract

Large language models are thought to have potential to aid in medical decision making. We investigate this here. We start with the treatment problem, the patient's core medical decision-making task, which is solved in collaboration with a healthcare provider. We discuss approaches to solving the treatment problem, including -- within evidence-based medicine -- trials and observational data. We then discuss the chat problem, and how this differs from the treatment problem -- in particular as it relates to imitation. We then discuss how a large language model might be used to solve the treatment problem and highlight some of the challenges that emerge. We finally discuss how these challenges relate to evidence-based medicine, and how this might inform next steps.

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Cite this paper

@article{weisenthal2025treatment,
  title  = {Treatment, evidence, imitation, and chat},
  author = {Samuel J. Weisenthal},
  year   = {2025},
  eprint = {2506.23040},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.23040v2}
}

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