Assessment of the Responses of the Artificial Intelligence–based Chatbot ChatGPT-4 to Frequently Asked Questions About Amblyopia and Childhood Myopia

斜视 医学 小兒眼科學 验光服务 折射误差 儿科 药方 眼科 眼病 药理学
作者
Mojgan Nikdel,Hadi Ghadimi,Mehdi Tavakoli,Donny W. Suh
出处
期刊:Journal of Pediatric Ophthalmology & Strabismus [Slack Incorporated (United States)]
卷期号:61 (2): 86-89 被引量:22
标识
DOI:10.3928/01913913-20231005-02
摘要

Purpose: To assess the responses of the ChatGPT-4, the forerunner artificial intelligence–based chatbot, to frequently asked questions regarding two common pediatric ophthalmologic disorders, amblyopia and childhood myopia. Methods: Twenty-seven questions about amblyopia and 28 questions about childhood myopia were asked of the ChatGPT twice (totally 110 questions). The responses were evaluated by two pediatric ophthalmologists as acceptable, incomplete, or unacceptable. Results: There was remarkable agreement (96.4%) between the two pediatric ophthalmologists on their assessment of the responses. Acceptable responses were provided by the ChatGPT to 93 of 110 (84.6%) questions in total (44 of 54 [81.5%] for amblyopia and 49 of 56 [87.5%] questions for childhood myopia). Seven of 54 (12.9%) responses to questions on amblyopia were graded as incomplete compared to 4 of 56 (7.1%) of questions on childhood myopia. The ChatGPT gave inappropriate responses to three questions about amblyopia (5.6%) and childhood myopia (5.4%). The most noticeable inappropriate responses were related to the definition of reverse amblyopia and the threshold of refractive error for prescription of spectacles to children with myopia. Conclusions: The ChatGPT has the potential to serve as an adjunct informational tool for pediatric ophthalmology patients and their caregivers by demonstrating a relatively good performance in answering 84.6% of the most frequently asked questions about amblyopia and childhood myopia. [ J Pediatr Ophthalmol Strabismus . 2024;61(2):86–89.]
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
荆佳怡发布了新的文献求助10
刚刚
刚刚
1秒前
认真骁发布了新的文献求助10
1秒前
大模型应助gfgDADA采纳,获得10
1秒前
huzihao发布了新的文献求助10
1秒前
2秒前
Gin发布了新的文献求助10
2秒前
3秒前
yufanhui完成签到,获得积分0
3秒前
青青发布了新的文献求助10
4秒前
4秒前
xiaofeifan发布了新的文献求助10
4秒前
4秒前
领导范儿应助66采纳,获得10
4秒前
4秒前
5秒前
zq完成签到 ,获得积分10
5秒前
mayu完成签到,获得积分10
5秒前
6秒前
orixero应助董雪采纳,获得10
7秒前
canghainayun完成签到,获得积分10
7秒前
Wangguagua发布了新的文献求助10
7秒前
7秒前
8秒前
Dr.lee完成签到,获得积分10
8秒前
杨纨成发布了新的文献求助10
8秒前
8秒前
KAER发布了新的文献求助10
8秒前
cdercder应助荆佳怡采纳,获得10
9秒前
无花果应助无奈的碧彤采纳,获得10
9秒前
整齐的夏柳完成签到,获得积分10
9秒前
10秒前
橙子发布了新的文献求助20
10秒前
cmuzf完成签到,获得积分10
11秒前
12秒前
在水一方应助认真骁采纳,获得10
12秒前
Criminology34应助史萌采纳,获得10
12秒前
13秒前
13秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7256030
求助须知:如何正确求助?哪些是违规求助? 8878049
关于积分的说明 18749848
捐赠科研通 6936182
什么是DOI,文献DOI怎么找? 3200647
关于科研通互助平台的介绍 2374946
邀请新用户注册赠送积分活动 2176062