Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study.

IF 3.2 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Fumitoshi Fukuzawa, Yasutaka Yanagita, Daiki Yokokawa, Shun Uchida, Shiho Yamashita, Yu Li, Kiyoshi Shikino, Tomoko Tsukamoto, Kazutaka Noda, Takanori Uehara, Masatomi Ikusaka
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引用次数: 0

Abstract

Background: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis.

Objective: This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided.

Methods: Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses.

Results: ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included.

Conclusions: Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems.

患者病史在人工智能辅助医疗诊断中的重要性:比较研究
背景:尽管体格检查和实验室检查能增强医生对医疗诊断的信心,但病史对诊断的影响约占 80%。人工智能(AI)的概念最早是在 70 多年前提出的。最近,人工智能在医学各领域的作用显著增强。然而,还没有研究评估过患者病史在人工智能辅助医疗诊断中的重要性:本研究探讨了患者病史对人工智能辅助医疗诊断的贡献,并评估了 ChatGPT 根据患者提供的病史做出临床诊断的准确性:我们使用《英国医学杂志》(The BMJ)上的 30 个临床病例,评估了 ChatGPT 得出的诊断结果的准确性。我们将 ChatGPT 仅根据病史做出的诊断与正确诊断进行了比较。我们还比较了 ChatGPT 在病史基础上结合其他体格检查结果和实验室数据得出的诊断结果与正确诊断结果:结果:仅凭病史,ChatGPT 就准确诊断出了 76.6% 的病例(23/30),这与之前针对医生的研究结果一致。我们还发现,在加入其他信息后,这一比例达到了 93.3%(28/30):结论:虽然增加额外信息能提高诊断准确性,但患者病史仍是人工智能辅助医疗诊断的一个重要因素。因此,在使用人工智能进行医疗诊断时,纳入相关且正确的病史对于准确诊断至关重要。我们的研究结果强调了患者病史在临床诊断中的重要性,并突出了将其纳入人工智能辅助医疗诊断系统的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR Medical Education
JMIR Medical Education Social Sciences-Education
CiteScore
6.90
自引率
5.60%
发文量
54
审稿时长
8 weeks
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