Performance of ChatGPT and GPT-4 on Neurosurgery Written Board Examinations

医学 神经外科 梅德林 医学物理学 放射科 政治学 法学
作者
Rohaid Ali,Oliver Y. Tang,Ian D. Connolly,Patricia L. Zadnik Sullivan,John H. Shin,Jared S. Fridley,Wael F. Asaad,Deus Cielo,Adetokunbo A. Oyelese,Curtis E. Doberstein,Ziya L. Gokaslan,Albert E. Telfeian
出处
期刊:Neurosurgery [Lippincott Williams & Wilkins]
被引量:143
标识
DOI:10.1227/neu.0000000000002632
摘要

Interest surrounding generative large language models (LLMs) has rapidly grown. Although ChatGPT (GPT-3.5), a general LLM, has shown near-passing performance on medical student board examinations, the performance of ChatGPT or its successor GPT-4 on specialized examinations and the factors affecting accuracy remain unclear. This study aims to assess the performance of ChatGPT and GPT-4 on a 500-question mock neurosurgical written board examination. The Self-Assessment Neurosurgery Examinations (SANS) American Board of Neurological Surgery Self-Assessment Examination 1 was used to evaluate ChatGPT and GPT-4. Questions were in single best answer, multiple-choice format. χ 2 , Fisher exact, and univariable logistic regression tests were used to assess performance differences in relation to question characteristics. ChatGPT (GPT-3.5) and GPT-4 achieved scores of 73.4% (95% CI: 69.3%-77.2%) and 83.4% (95% CI: 79.8%-86.5%), respectively, relative to the user average of 72.8% (95% CI: 68.6%-76.6%). Both LLMs exceeded last year's passing threshold of 69%. Although scores between ChatGPT and question bank users were equivalent ( P = .963), GPT-4 outperformed both (both P < .001). GPT-4 answered every question answered correctly by ChatGPT and 37.6% (50/133) of remaining incorrect questions correctly. Among 12 question categories, GPT-4 significantly outperformed users in each but performed comparably with ChatGPT in 3 (functional, other general, and spine) and outperformed both users and ChatGPT for tumor questions. Increased word count (odds ratio = 0.89 of answering a question correctly per +10 words) and higher-order problem-solving (odds ratio = 0.40, P = .009) were associated with lower accuracy for ChatGPT, but not for GPT-4 (both P > .005). Multimodal input was not available at the time of this study; hence, on questions with image content, ChatGPT and GPT-4 answered 49.5% and 56.8% of questions correctly based on contextual context clues alone. LLMs achieved passing scores on a mock 500-question neurosurgical written board examination, with GPT-4 significantly outperforming ChatGPT.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wwww完成签到 ,获得积分10
刚刚
YixiaoWang发布了新的文献求助10
刚刚
量子星尘发布了新的文献求助10
1秒前
cr完成签到,获得积分10
1秒前
威武鸽子完成签到,获得积分20
1秒前
包容可仁完成签到,获得积分10
1秒前
拼搏绿柳完成签到,获得积分10
2秒前
开心的紫烟完成签到,获得积分10
2秒前
wdy111应助淡漠采纳,获得20
2秒前
2秒前
水吉2000完成签到,获得积分10
2秒前
3秒前
Owen应助zzzzz采纳,获得30
3秒前
CSPC001完成签到 ,获得积分10
4秒前
ForZero发布了新的文献求助10
4秒前
4秒前
5秒前
5秒前
5秒前
6秒前
乐乐应助鳗鱼灵寒采纳,获得10
6秒前
资山雁完成签到 ,获得积分10
7秒前
田様应助YixiaoWang采纳,获得10
7秒前
7秒前
ZJJ完成签到,获得积分20
7秒前
8秒前
大薯条完成签到 ,获得积分10
8秒前
one发布了新的文献求助10
8秒前
JoshuaChen发布了新的文献求助10
9秒前
锥子完成签到,获得积分10
9秒前
追风少侠李二狗完成签到,获得积分10
9秒前
10秒前
ZJJ发布了新的文献求助10
10秒前
CAOHOU应助nature采纳,获得20
10秒前
踹脸大妈发布了新的文献求助30
10秒前
Jenaloe发布了新的文献求助10
11秒前
巴斯光年发布了新的文献求助10
11秒前
完美世界应助科研通管家采纳,获得10
12秒前
water应助科研通管家采纳,获得10
12秒前
Lucas应助科研通管家采纳,获得10
12秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 330
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
Aktuelle Entwicklungen in der linguistischen Forschung 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3986722
求助须知:如何正确求助?哪些是违规求助? 3529207
关于积分的说明 11243810
捐赠科研通 3267638
什么是DOI,文献DOI怎么找? 1803822
邀请新用户注册赠送积分活动 881207
科研通“疑难数据库(出版商)”最低求助积分说明 808582