Enhancing clinical reasoning with Chat Generative Pre-trained Transformer: a practical guide

被引:5
|
作者
Hirosawa, Takanobu [1 ]
Shimizu, Taro [1 ]
机构
[1] Dokkyo Med Univ, Dept Diagnost & Generalist Med, 880 Kitakobayashi, Mibu Cho, Mibu, Tochigi 3210293, Japan
关键词
natural language processing; large language model; diagnostic excellence; diagnosis; self-learning;
D O I
10.1515/dx-2023-0116
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objectives: This study aimed to elucidate effective methodologies for utilizing the generative artificial intelligence (AI) system, namely the Chat Generative Pre-trained Transformer (ChatGPT), in improving clinical reasoning abilities among clinicians.Methods: We conducted a comprehensive exploration of the capabilities of ChatGPT, emphasizing two main areas: (1) efficient utilization of ChatGPT, with a focus on application and language selection, input methodology, and output verification; and (2) specific strategies to bolster clinical reasoning using ChatGPT, including self-learning via simulated clinical case creation and engagement with published case reports.Results: Effective AI-based clinical reasoning development requires a clear delineation of both system roles and user needs. All outputs from the system necessitate rigorous verification against credible medical resources. When used in self-learning scenarios, capabilities of ChatGPT in clinical case creation notably enhanced disease comprehension.Conclusions: The efficient use of generative AIs, as exemplified by ChatGPT, can impressively enhance clinical reasoning among medical professionals. Adopting these cutting-edge tools promises a bright future for continuous advancements in clinicians' diagnostic skills, heralding a transformative era in digital healthcare.
引用
收藏
页码:102 / 105
页数:4
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