Unveiling the risks of ChatGPT in diagnostic surgical pathologyChatGPT

IF 3.4 3区 医学 Q1 PATHOLOGY
Vincenzo Guastafierro, Devin N. Corbitt, Alessandra Bressan, Bethania Fernandes, Ömer Mintemur, Francesca Magnoli, Susanna Ronchi, Stefano La Rosa, Silvia Uccella, Salvatore Lorenzo Renne
{"title":"Unveiling the risks of ChatGPT in diagnostic surgical pathologyChatGPT","authors":"Vincenzo Guastafierro, Devin N. Corbitt, Alessandra Bressan, Bethania Fernandes, Ömer Mintemur, Francesca Magnoli, Susanna Ronchi, Stefano La Rosa, Silvia Uccella, Salvatore Lorenzo Renne","doi":"10.1007/s00428-024-03918-1","DOIUrl":null,"url":null,"abstract":"<p>ChatGPT, an AI capable of processing and generating human-like language, has been studied in medical education and care, yet its potential in histopathological diagnosis remains unexplored. This study evaluates ChatGPT’s reliability in addressing pathology-related diagnostic questions across ten subspecialties and its ability to provide scientific references. We crafted five clinico-pathological scenarios per subspecialty, simulating a pathologist using ChatGPT to refine differential diagnoses. Each scenario, aligned with current diagnostic guidelines and validated by expert pathologists, was posed as open-ended or multiple-choice questions, either requesting scientific references or not. Outputs were assessed by six pathologists according to. (1) usefulness in supporting the diagnosis and (2) absolute number of errors. We used directed acyclic graphs and structural causal models to determine the effect of each scenario type, field, question modality, and pathologist evaluation. We yielded 894 evaluations. ChatGPT provided useful answers in 62.2% of cases, and 32.1% of outputs contained no errors, while the remaining had at least one error. ChatGPT provided 214 bibliographic references: 70.1% correct, 12.1% inaccurate, and 17.8% non-existing. Scenario variability had the greatest impact on ratings, and latent knowledge across fields showed minimal variation. Although ChatGPT provided useful responses in one-third of cases, the frequency of errors and variability underscores its inadequacy for routine diagnostic use and highlights the need for discretion as a support tool. Imprecise referencing also suggests caution as a self-learning tool. It is essential to recognize the irreplaceable role of human experts in synthesizing images, clinical data, and experience for the intricate task of histopathological diagnosis.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\n","PeriodicalId":23514,"journal":{"name":"Virchows Archiv","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virchows Archiv","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00428-024-03918-1","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

ChatGPT, an AI capable of processing and generating human-like language, has been studied in medical education and care, yet its potential in histopathological diagnosis remains unexplored. This study evaluates ChatGPT’s reliability in addressing pathology-related diagnostic questions across ten subspecialties and its ability to provide scientific references. We crafted five clinico-pathological scenarios per subspecialty, simulating a pathologist using ChatGPT to refine differential diagnoses. Each scenario, aligned with current diagnostic guidelines and validated by expert pathologists, was posed as open-ended or multiple-choice questions, either requesting scientific references or not. Outputs were assessed by six pathologists according to. (1) usefulness in supporting the diagnosis and (2) absolute number of errors. We used directed acyclic graphs and structural causal models to determine the effect of each scenario type, field, question modality, and pathologist evaluation. We yielded 894 evaluations. ChatGPT provided useful answers in 62.2% of cases, and 32.1% of outputs contained no errors, while the remaining had at least one error. ChatGPT provided 214 bibliographic references: 70.1% correct, 12.1% inaccurate, and 17.8% non-existing. Scenario variability had the greatest impact on ratings, and latent knowledge across fields showed minimal variation. Although ChatGPT provided useful responses in one-third of cases, the frequency of errors and variability underscores its inadequacy for routine diagnostic use and highlights the need for discretion as a support tool. Imprecise referencing also suggests caution as a self-learning tool. It is essential to recognize the irreplaceable role of human experts in synthesizing images, clinical data, and experience for the intricate task of histopathological diagnosis.

Graphical Abstract

Abstract Image

求助全文
约1分钟内获得全文 求助全文
来源期刊
Virchows Archiv
Virchows Archiv 医学-病理学
CiteScore
7.40
自引率
2.90%
发文量
204
审稿时长
4-8 weeks
期刊介绍: Manuscripts of original studies reinforcing the evidence base of modern diagnostic pathology, using immunocytochemical, molecular and ultrastructural techniques, will be welcomed. In addition, papers on critical evaluation of diagnostic criteria but also broadsheets and guidelines with a solid evidence base will be considered. Consideration will also be given to reports of work in other fields relevant to the understanding of human pathology as well as manuscripts on the application of new methods and techniques in pathology. Submission of purely experimental articles is discouraged but manuscripts on experimental work applicable to diagnostic pathology are welcomed. Biomarker studies are welcomed but need to abide by strict rules (e.g. REMARK) of adequate sample size and relevant marker choice. Single marker studies on limited patient series without validated application will as a rule not be considered. Case reports will only be considered when they provide substantial new information with an impact on understanding disease or diagnostic practice.
文献相关原料
公司名称 产品信息 采购帮参考价格
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信