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Licensed Unlicensed Requires Authentication Published by De Gruyter October 3, 2023

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

  • Takanobu Hirosawa ORCID logo EMAIL logo and Taro Shimizu
From the journal Diagnosis

Abstract

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.


Corresponding author: Takanobu Hirosawa, MD, PhD, Department of Diagnostic and Generalist Medicine, Dokkyo Medical University, 880 Kitakobayashi, Mibu-cho, Simotsuga-gun, Tochigi 321-0293, Japan, Phone: +81-282-86-1111, Fax: +81-282-86-4775, E-mail:

Acknowledgments

This study was made possible using the resources from the Department of Diagnostic and Generalist Medicine, Dokkyo Medical University.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: None declared.

  6. Data availability: Not applicable.

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Received: 2023-08-30
Accepted: 2023-09-04
Published Online: 2023-10-03

© 2023 Walter de Gruyter GmbH, Berlin/Boston

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