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

IF 2.2 Q2 MEDICINE, GENERAL & INTERNAL Diagnosis Pub Date : 2023-10-03 eCollection Date: 2024-02-01 DOI:10.1515/dx-2023-0116
Takanobu Hirosawa, Taro Shimizu
{"title":"Enhancing clinical reasoning with Chat Generative Pre-trained Transformer: a practical guide.","authors":"Takanobu Hirosawa, Taro Shimizu","doi":"10.1515/dx-2023-0116","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":"102-105"},"PeriodicalIF":2.2000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnosis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/dx-2023-0116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用Chat Generative预训练Transformer增强临床推理:实用指南。
目的:本研究旨在阐明利用生成人工智能(AI)系统,即聊天生成预训练转换器(ChatGPT),提高临床医生临床推理能力的有效方法。方法:我们对ChatGPT的能力进行了全面的探索,强调了两个主要领域:(1)ChatGPT高效利用,重点是应用和语言选择、输入方法和输出验证;以及(2)使用ChatGPT支持临床推理的具体策略,包括通过模拟临床病例创建和参与已发布的病例报告进行自我学习。结果:有效的基于人工智能的临床推理开发需要清楚地描述系统角色和用户需求。该系统的所有产出都需要对可靠的医疗资源进行严格核查。当用于自学习场景时,ChatGPT在临床病例创建中的能力显著增强了对疾病的理解。结论:以ChatGPT为例,有效使用生成性人工智能可以显著提高医学专业人员的临床推理能力。采用这些尖端工具有望为临床医生诊断技能的不断进步带来光明的未来,预示着数字医疗的变革时代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Diagnosis
Diagnosis MEDICINE, GENERAL & INTERNAL-
CiteScore
7.20
自引率
5.70%
发文量
41
期刊介绍: Diagnosis focuses on how diagnosis can be advanced, how it is taught, and how and why it can fail, leading to diagnostic errors. The journal welcomes both fundamental and applied works, improvement initiatives, opinions, and debates to encourage new thinking on improving this critical aspect of healthcare quality.  Topics: -Factors that promote diagnostic quality and safety -Clinical reasoning -Diagnostic errors in medicine -The factors that contribute to diagnostic error: human factors, cognitive issues, and system-related breakdowns -Improving the value of diagnosis – eliminating waste and unnecessary testing -How culture and removing blame promote awareness of diagnostic errors -Training and education related to clinical reasoning and diagnostic skills -Advances in laboratory testing and imaging that improve diagnostic capability -Local, national and international initiatives to reduce diagnostic error
期刊最新文献
Time pressure in diagnosing written clinical cases: an experimental study on time constraints and perceived time pressure. CDC's Core Elements to promote diagnostic excellence. Trends of diagnostic adverse events in hospital deaths: longitudinal analyses of four retrospective record review studies. A decision support system to increase the compliance of diagnostic imaging examinations with imaging guidelines: focused on cerebrovascular diseases. Bayesian intelligence for medical diagnosis: a pilot study on patient disposition for emergency medicine chest pain.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1