Max Samuel Yudovich, Elizaveta Makarova, Christian Michael Hague, Jay Dilip Raman
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GPT-4 (vs. GPT-3.5) had higher accuracy with urologic oncology (43.8% vs. 33.9%, P=0.03), sexual medicine (44.3% vs. 27.8%, P=0.046), and pediatric urology (47.1% vs. 27.1%, P=0.012) items. Endourology (38.0% vs. 25.7%, P=0.15), reconstruction and trauma (29.0% vs. 21.0%, P=0.41), and neurourology (49.0% vs. 33.3%, P=0.11) items did not show significant differences in performance across versions. GPT-4 also outperformed GPT-3.5 with respect to recall (45.9% vs. 27.4%, P<0.00001), interpretation (45.6% vs. 31.5%, P=0.0005), and problem-solving (41.8% vs. 34.5%, P=0.56) type items. This difference was not significant for the higher-complexity items.</p><p><strong>Conclusion: </strong>s: ChatGPT performs relatively poorly on standardized multiple-choice urology board exam-style items, with GPT-4 outperforming GPT-3.5. The accuracy was below the proposed minimum passing standards for the American Board of Urology's Continuing Urologic Certification knowledge reinforcement activity (60%). As artificial intelligence progresses in complexity, ChatGPT may become more capable and accurate with respect to board examination items. For now, its responses should be scrutinized.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"21 ","pages":"17"},"PeriodicalIF":9.3000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of GPT-3.5 and GPT-4 on standardized urology knowledge assessment items in the United States: a descriptive study.\",\"authors\":\"Max Samuel Yudovich, Elizaveta Makarova, Christian Michael Hague, Jay Dilip Raman\",\"doi\":\"10.3352/jeehp.2024.21.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>This study aimed to evaluate the performance of Chat Generative Pre-Trained Transformer (ChatGPT) with respect to standardized urology multiple-choice items in the United States.</p><p><strong>Methods: </strong>In total, 700 multiple-choice urology board exam-style items were submitted to GPT-3.5 and GPT-4, and responses were recorded. 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引用次数: 0
摘要
目的:本研究旨在评估 Chat Generative Pre-Trained Transformer(ChatGPT)在美国标准化泌尿科选择题方面的性能:共向 GPT-3.5 和 GPT-4 提交了 700 个泌尿外科委员会考试类型的多项选择题,并记录了答案。根据题目和问题复杂程度(回忆、解释和解决问题)对项目进行分类。2024 年 2 月,比较了 GPT-3.5 和 GPT-4 在不同项目类型中的准确性:结果:GPT-4 回答正确率为 44.4%,而 GPT-3.5 为 30.9%(P>0.0001)。GPT-4(vs.GPT-3.5)在泌尿肿瘤学(43.8% vs. 33.9%,P=0.03)、性医学(44.3% vs. 27.8%,P=0.046)和小儿泌尿学(47.1% vs. 27.1%,P=0.012)项目上的准确率更高。内泌尿学(38.0% vs. 25.7%,P=0.15)、重建与创伤(29.0% vs. 21.0%,P=0.41)和神经泌尿学(49.0% vs. 33.3%,P=0.11)项目在不同版本中的表现没有显著差异。在回忆率方面,GPT-4 也优于 GPT-3.5(45.9% 对 27.4%,P=0.41):ChatGPT 在标准化的泌尿外科医师资格考试多选题上的表现相对较差,GPT-4 的表现优于 GPT-3.5。准确率低于美国泌尿外科委员会泌尿外科继续认证知识强化活动的最低合格标准(60%)。随着人工智能复杂性的提高,ChatGPT 在委员会考试项目方面的能力和准确性可能会越来越高。就目前而言,应该对它的回答进行仔细检查。
Performance of GPT-3.5 and GPT-4 on standardized urology knowledge assessment items in the United States: a descriptive study.
Purpose: This study aimed to evaluate the performance of Chat Generative Pre-Trained Transformer (ChatGPT) with respect to standardized urology multiple-choice items in the United States.
Methods: In total, 700 multiple-choice urology board exam-style items were submitted to GPT-3.5 and GPT-4, and responses were recorded. Items were categorized based on topic and question complexity (recall, interpretation, and problem-solving). The accuracy of GPT-3.5 and GPT-4 was compared across item types in February 2024.
Results: GPT-4 answered 44.4% of items correctly compared to 30.9% for GPT-3.5 (P>0.0001). GPT-4 (vs. GPT-3.5) had higher accuracy with urologic oncology (43.8% vs. 33.9%, P=0.03), sexual medicine (44.3% vs. 27.8%, P=0.046), and pediatric urology (47.1% vs. 27.1%, P=0.012) items. Endourology (38.0% vs. 25.7%, P=0.15), reconstruction and trauma (29.0% vs. 21.0%, P=0.41), and neurourology (49.0% vs. 33.3%, P=0.11) items did not show significant differences in performance across versions. GPT-4 also outperformed GPT-3.5 with respect to recall (45.9% vs. 27.4%, P<0.00001), interpretation (45.6% vs. 31.5%, P=0.0005), and problem-solving (41.8% vs. 34.5%, P=0.56) type items. This difference was not significant for the higher-complexity items.
Conclusion: s: ChatGPT performs relatively poorly on standardized multiple-choice urology board exam-style items, with GPT-4 outperforming GPT-3.5. The accuracy was below the proposed minimum passing standards for the American Board of Urology's Continuing Urologic Certification knowledge reinforcement activity (60%). As artificial intelligence progresses in complexity, ChatGPT may become more capable and accurate with respect to board examination items. For now, its responses should be scrutinized.
期刊介绍:
Journal of Educational Evaluation for Health Professions aims to provide readers the state-of-the art practical information on the educational evaluation for health professions so that to increase the quality of undergraduate, graduate, and continuing education. It is specialized in educational evaluation including adoption of measurement theory to medical health education, promotion of high stakes examination such as national licensing examinations, improvement of nationwide or international programs of education, computer-based testing, computerized adaptive testing, and medical health regulatory bodies. Its field comprises a variety of professions that address public medical health as following but not limited to: Care workers Dental hygienists Dental technicians Dentists Dietitians Emergency medical technicians Health educators Medical record technicians Medical technologists Midwives Nurses Nursing aides Occupational therapists Opticians Oriental medical doctors Oriental medicine dispensers Oriental pharmacists Pharmacists Physical therapists Physicians Prosthetists and Orthotists Radiological technologists Rehabilitation counselor Sanitary technicians Speech-language therapists.