Amplifying Chinese physicians’ emphasis on patients’ psychological states beyond urologic diagnoses with ChatGPT—A multi-center cross-sectional study

医学 重点(电信) 中心(范畴论) 医学诊断 横断面研究 家庭医学 普通外科 病理 结晶学 电气工程 工程类 化学
作者
Peng Lei,Rui Liang,Aiping Zhao,Ruonan Sun,Fulin Yi,Jianye Zhong,Rongkang Li,Shanyuan Zhu,Shaohua Zhang,Song Wu
出处
期刊:International Journal of Surgery [Elsevier]
标识
DOI:10.1097/js9.0000000000001775
摘要

Background: Artificial intelligence (AI) technologies, particularly large language models (LLMs), have been widely employed by the medical community. In addressing the intricacies of urology, ChatGPT offers a novel possibility to aid in clinical decision-making. This study aimed to investigate the decision-making ability of LLMs in solving complex urology-related problems and assess its effectiveness in providing psychological support to patients with urological disorders. Materials and Methods: This study evaluated the clinical and psychological support capabilities of ChatGPT 3.5 and 4.0 in the field of urology. A total of 69 clinical and 30 psychological questions were posed to the AI models, and their responses were evaluated by both urologists and psychologists. As a control, clinicians from Chinese medical institutions provided responses under closed-book conditions. Statistical analyses were conducted separately for each subgroup. Results: In multiple-choice tests covering diverse urological topics, ChatGPT 4.0, performed comparably to the physician group, with no significant overall score difference. Subgroup analyses revealed variable performance, based on disease type and physician experience, with ChatGPT 4.0 generally outperforming ChatGPT 3.5 and exhibiting competitive results against physicians. When assessing the psychological support capabilities of AI, it is evident that ChatGPT4.0 outperforms ChatGPT3.5 across all urology-related psychological problems. Conclusions: The performance of LLMs in dealing with standardized clinical problems and providing psychological support has certain advantages over clinicians. AI stands out as a promising tool for potential clinical aid.
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
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
777完成签到,获得积分10
刚刚
1秒前
1秒前
黄丽军发布了新的文献求助10
1秒前
1秒前
1秒前
2秒前
小彻完成签到,获得积分10
2秒前
慕青应助研友_nxGqeL采纳,获得20
2秒前
2秒前
3秒前
shang发布了新的文献求助10
3秒前
Giroro_roro完成签到,获得积分10
3秒前
4秒前
完美世界应助橘子采纳,获得10
4秒前
三口发布了新的文献求助10
4秒前
CipherSage应助lisali采纳,获得10
5秒前
夏天来了发布了新的文献求助30
5秒前
dmj发布了新的文献求助10
5秒前
完美世界应助绿夏采纳,获得30
5秒前
dong发布了新的文献求助10
6秒前
ssssssssci完成签到,获得积分10
6秒前
6秒前
7秒前
牛牛发布了新的文献求助10
7秒前
思源应助初晴采纳,获得10
7秒前
景木游发布了新的文献求助10
8秒前
roy_chiang发布了新的文献求助10
9秒前
勤劳影子发布了新的文献求助10
9秒前
英俊的铭应助难得糊涂zq采纳,获得10
9秒前
ming完成签到,获得积分10
9秒前
9秒前
Damon完成签到,获得积分20
10秒前
水下月完成签到,获得积分10
11秒前
Phoebe发布了新的文献求助10
11秒前
neeeru完成签到,获得积分10
11秒前
uu发布了新的文献求助10
11秒前
12秒前
星辰大海应助Mr_clf采纳,获得10
13秒前
追寻凌晴完成签到,获得积分10
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 1000
Conference Record, IAS Annual Meeting 1977 710
電気学会論文誌D(産業応用部門誌), 141 巻, 11 号 510
Virulence Mechanisms of Plant-Pathogenic Bacteria 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3564116
求助须知:如何正确求助?哪些是违规求助? 3137325
关于积分的说明 9421827
捐赠科研通 2837701
什么是DOI,文献DOI怎么找? 1559976
邀请新用户注册赠送积分活动 729224
科研通“疑难数据库(出版商)”最低求助积分说明 717246