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。

诊断推理提示揭示了在医学领域中大型语言模型可解释性的潜力