gpt - 40能准确诊断创伤x光吗?与专家评价的比较研究。

IF 1.2 4区 医学 Q3 EMERGENCY MEDICINE
Ahmet Öztürk MD , Serkan Günay MD , Serdal Ateş MD , Yavuz Yiğit (Yavuz Yigit) MD
{"title":"gpt - 40能准确诊断创伤x光吗?与专家评价的比较研究。","authors":"Ahmet Öztürk MD ,&nbsp;Serkan Günay MD ,&nbsp;Serdal Ateş MD ,&nbsp;Yavuz Yiğit (Yavuz Yigit) MD","doi":"10.1016/j.jemermed.2024.12.010","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process visual data, presenting a novel opportunity for radiographic evaluation in trauma patients.</div></div><div><h3>Objective</h3><div>This study aimed to assess the efficacy of GPT-4o in interpreting radiographs for traumatic bone pathologies and to compare its performance with that of emergency medicine and orthopedic specialists.</div></div><div><h3>Methods</h3><div>The study involved 10 emergency medicine specialists, 10 orthopedic specialists, and the GPT-4o AI model, evaluating 25 cases of traumatic bone pathologies of the upper and lower extremities selected from the Radiopaedia website. Participants were asked to identify fractures or dislocations in the radiographs within 45 minutes. GPT-4o was instructed to perform the same task in 10 different chat sessions.</div></div><div><h3>Results</h3><div>Emergency medicine specialists and orthopedic specialists demonstrated an average accuracy of 82.8% and 87.2%, respectively, in radiograph interpretation. In contrast, GPT-4o achieved an accuracy of only 11.2%. Statistical analysis revealed significant differences among the three groups (<em>p</em> &lt; 0.001), with GPT-4o performing significantly worse than both groups of specialists.</div></div><div><h3>Conclusion</h3><div>GPT-4o's ability to interpret radiographs of traumatic bone pathologies is currently limited and significantly inferior to that of trained specialists. These findings underscore the ongoing need for human expertise in trauma diagnosis and highlight the challenges of applying AI to complex medical imaging tasks.</div></div>","PeriodicalId":16085,"journal":{"name":"Journal of Emergency Medicine","volume":"73 ","pages":"Pages 71-79"},"PeriodicalIF":1.2000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can Gpt-4o Accurately Diagnose Trauma X-Rays? A Comparative Study with Expert Evaluations\",\"authors\":\"Ahmet Öztürk MD ,&nbsp;Serkan Günay MD ,&nbsp;Serdal Ateş MD ,&nbsp;Yavuz Yiğit (Yavuz Yigit) MD\",\"doi\":\"10.1016/j.jemermed.2024.12.010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process visual data, presenting a novel opportunity for radiographic evaluation in trauma patients.</div></div><div><h3>Objective</h3><div>This study aimed to assess the efficacy of GPT-4o in interpreting radiographs for traumatic bone pathologies and to compare its performance with that of emergency medicine and orthopedic specialists.</div></div><div><h3>Methods</h3><div>The study involved 10 emergency medicine specialists, 10 orthopedic specialists, and the GPT-4o AI model, evaluating 25 cases of traumatic bone pathologies of the upper and lower extremities selected from the Radiopaedia website. Participants were asked to identify fractures or dislocations in the radiographs within 45 minutes. GPT-4o was instructed to perform the same task in 10 different chat sessions.</div></div><div><h3>Results</h3><div>Emergency medicine specialists and orthopedic specialists demonstrated an average accuracy of 82.8% and 87.2%, respectively, in radiograph interpretation. In contrast, GPT-4o achieved an accuracy of only 11.2%. Statistical analysis revealed significant differences among the three groups (<em>p</em> &lt; 0.001), with GPT-4o performing significantly worse than both groups of specialists.</div></div><div><h3>Conclusion</h3><div>GPT-4o's ability to interpret radiographs of traumatic bone pathologies is currently limited and significantly inferior to that of trained specialists. These findings underscore the ongoing need for human expertise in trauma diagnosis and highlight the challenges of applying AI to complex medical imaging tasks.</div></div>\",\"PeriodicalId\":16085,\"journal\":{\"name\":\"Journal of Emergency Medicine\",\"volume\":\"73 \",\"pages\":\"Pages 71-79\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Emergency Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0736467924004037\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"EMERGENCY MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Emergency Medicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736467924004037","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0

摘要

背景:OpenAI公司推出的最新人工智能(AI)模型gpt - 40可以处理视觉数据,为创伤患者的放射学评估提供了新的机会。目的:本研究旨在评估gpt - 40在创伤性骨病理x线片解释中的作用,并将其与急诊医学和骨科专家的表现进行比较。方法:采用10名急诊医学专家、10名骨科专家和gpt - 40ai模型,对从Radiopaedia网站上选取的25例上肢和下肢外伤性骨病理病例进行评估。参与者被要求在45分钟内在x线片上识别骨折或脱位。gpt - 40被要求在10个不同的聊天会话中执行相同的任务。结果:急诊医学专家和骨科专家在x线片解释上的平均准确率分别为82.8%和87.2%。相比之下,gpt - 40的准确率仅为11.2%。统计分析显示三组之间存在显著差异(p < 0.001), gpt - 40的表现明显低于两组专家。结论:gpt - 40对创伤性骨病理x线片的解读能力目前是有限的,明显不如训练有素的专家。这些发现强调了在创伤诊断方面对人类专业知识的持续需求,并强调了将人工智能应用于复杂医学成像任务的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Can Gpt-4o Accurately Diagnose Trauma X-Rays? A Comparative Study with Expert Evaluations

Background

The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process visual data, presenting a novel opportunity for radiographic evaluation in trauma patients.

Objective

This study aimed to assess the efficacy of GPT-4o in interpreting radiographs for traumatic bone pathologies and to compare its performance with that of emergency medicine and orthopedic specialists.

Methods

The study involved 10 emergency medicine specialists, 10 orthopedic specialists, and the GPT-4o AI model, evaluating 25 cases of traumatic bone pathologies of the upper and lower extremities selected from the Radiopaedia website. Participants were asked to identify fractures or dislocations in the radiographs within 45 minutes. GPT-4o was instructed to perform the same task in 10 different chat sessions.

Results

Emergency medicine specialists and orthopedic specialists demonstrated an average accuracy of 82.8% and 87.2%, respectively, in radiograph interpretation. In contrast, GPT-4o achieved an accuracy of only 11.2%. Statistical analysis revealed significant differences among the three groups (p < 0.001), with GPT-4o performing significantly worse than both groups of specialists.

Conclusion

GPT-4o's ability to interpret radiographs of traumatic bone pathologies is currently limited and significantly inferior to that of trained specialists. These findings underscore the ongoing need for human expertise in trauma diagnosis and highlight the challenges of applying AI to complex medical imaging tasks.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Emergency Medicine
Journal of Emergency Medicine 医学-急救医学
CiteScore
2.40
自引率
6.70%
发文量
339
审稿时长
2-4 weeks
期刊介绍: The Journal of Emergency Medicine is an international, peer-reviewed publication featuring original contributions of interest to both the academic and practicing emergency physician. JEM, published monthly, contains research papers and clinical studies as well as articles focusing on the training of emergency physicians and on the practice of emergency medicine. The Journal features the following sections: • Original Contributions • Clinical Communications: Pediatric, Adult, OB/GYN • Selected Topics: Toxicology, Prehospital Care, The Difficult Airway, Aeromedical Emergencies, Disaster Medicine, Cardiology Commentary, Emergency Radiology, Critical Care, Sports Medicine, Wound Care • Techniques and Procedures • Technical Tips • Clinical Laboratory in Emergency Medicine • Pharmacology in Emergency Medicine • Case Presentations of the Harvard Emergency Medicine Residency • Visual Diagnosis in Emergency Medicine • Medical Classics • Emergency Forum • Editorial(s) • Letters to the Editor • Education • Administration of Emergency Medicine • International Emergency Medicine • Computers in Emergency Medicine • Violence: Recognition, Management, and Prevention • Ethics • Humanities and Medicine • American Academy of Emergency Medicine • AAEM Medical Student Forum • Book and Other Media Reviews • Calendar of Events • Abstracts • Trauma Reports • Ultrasound in Emergency Medicine
×
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:604180095
Book学术官方微信