One of the major barriers to using large language models (LLMs) in medicine
is the perception they use uninterpretable methods to make clinical decisions
that are inherently different from the cognitive processes of clinicians. In
this manuscript we develop novel diagnostic reasoning prompts to study whether
LLMs can perform clinical reasoning to accurately form a diagnosis. We find
that GPT4 can be prompted to mimic the common clinical reasoning processes of
clinicians without sacrificing diagnostic accuracy. This is significant because
an LLM that can use clinical reasoning to provide an interpretable rationale
offers physicians a means to evaluate whether LLMs can be trusted for patient
care. Novel prompting methods have the potential to expose the black box of
LLMs, bringing them one step closer to safe and effective use in medicine.

GPT4 可以通过使用诊断推理提示模拟临床医生的常见临床推理过程，而不会损失诊断准确性，因此它可以为医生提供评估 LLMs 是否可信赖用于患者护理的手段。新的提示方法有潜力揭示 LLMs 的黑盒子，将它们推向在医学中安全有效使用的一步。