人工智能聊天机器人在解读压力损伤临床图像中的表现。

IF 3.8 3区 医学 Q2 CELL BIOLOGY Wound Repair and Regeneration Pub Date : 2024-05-15 DOI:10.1111/wrr.13189
Makoto Shiraishi, Koji Kanayama, Daichi Kurita, Yuta Moriwaki, Mutsumi Okazaki
{"title":"人工智能聊天机器人在解读压力损伤临床图像中的表现。","authors":"Makoto Shiraishi, Koji Kanayama, Daichi Kurita, Yuta Moriwaki, Mutsumi Okazaki","doi":"10.1111/wrr.13189","DOIUrl":null,"url":null,"abstract":"<p><p>To evaluate the accuracy of AI chatbots in staging pressure injuries according to the National Pressure Injury Advisory Panel (NPIAP) Staging through clinical image interpretation, a cross-sectional design was conducted to assess five leading publicly available AI chatbots. As a result, three chatbots were unable to interpret the clinical images, whereas GPT-4 Turbo achieved a high accuracy rate (83.0%) in staging pressure injuries, notably outperforming BingAI Creative mode (24.0%) with statistical significance (p < 0.001). GPT-4 Turbo accurately identified Stages 1 (p < 0.001), 3 (p = 0.001), and 4 (p < 0.001) pressure injuries, and suspected deep tissue injuries (p < 0.001), while BingAI demonstrated significantly lower accuracy across all stages. The findings highlight the potential of AI chatbots, especially GPT-4 Turbo, in accurately diagnosing images and aiding the subsequent management of pressure injuries.</p>","PeriodicalId":23864,"journal":{"name":"Wound Repair and Regeneration","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of artificial intelligence chatbots in interpreting clinical images of pressure injuries.\",\"authors\":\"Makoto Shiraishi, Koji Kanayama, Daichi Kurita, Yuta Moriwaki, Mutsumi Okazaki\",\"doi\":\"10.1111/wrr.13189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>To evaluate the accuracy of AI chatbots in staging pressure injuries according to the National Pressure Injury Advisory Panel (NPIAP) Staging through clinical image interpretation, a cross-sectional design was conducted to assess five leading publicly available AI chatbots. As a result, three chatbots were unable to interpret the clinical images, whereas GPT-4 Turbo achieved a high accuracy rate (83.0%) in staging pressure injuries, notably outperforming BingAI Creative mode (24.0%) with statistical significance (p < 0.001). GPT-4 Turbo accurately identified Stages 1 (p < 0.001), 3 (p = 0.001), and 4 (p < 0.001) pressure injuries, and suspected deep tissue injuries (p < 0.001), while BingAI demonstrated significantly lower accuracy across all stages. The findings highlight the potential of AI chatbots, especially GPT-4 Turbo, in accurately diagnosing images and aiding the subsequent management of pressure injuries.</p>\",\"PeriodicalId\":23864,\"journal\":{\"name\":\"Wound Repair and Regeneration\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wound Repair and Regeneration\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/wrr.13189\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wound Repair and Regeneration","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/wrr.13189","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

为了评估人工智能聊天机器人根据国家压力伤害顾问团(NPIAP)通过临床图像判读进行压力伤害分期的准确性,我们采用横断面设计评估了五款领先的公开人工智能聊天机器人。结果发现,有三个聊天机器人无法解读临床图像,而 GPT-4 Turbo 在压力损伤分期方面达到了很高的准确率(83.0%),明显优于 BingAI Creative 模式(24.0%),且具有统计学意义(p<0.05)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Performance of artificial intelligence chatbots in interpreting clinical images of pressure injuries.

To evaluate the accuracy of AI chatbots in staging pressure injuries according to the National Pressure Injury Advisory Panel (NPIAP) Staging through clinical image interpretation, a cross-sectional design was conducted to assess five leading publicly available AI chatbots. As a result, three chatbots were unable to interpret the clinical images, whereas GPT-4 Turbo achieved a high accuracy rate (83.0%) in staging pressure injuries, notably outperforming BingAI Creative mode (24.0%) with statistical significance (p < 0.001). GPT-4 Turbo accurately identified Stages 1 (p < 0.001), 3 (p = 0.001), and 4 (p < 0.001) pressure injuries, and suspected deep tissue injuries (p < 0.001), while BingAI demonstrated significantly lower accuracy across all stages. The findings highlight the potential of AI chatbots, especially GPT-4 Turbo, in accurately diagnosing images and aiding the subsequent management of pressure injuries.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Wound Repair and Regeneration
Wound Repair and Regeneration 医学-皮肤病学
CiteScore
5.90
自引率
3.40%
发文量
71
审稿时长
6-12 weeks
期刊介绍: Wound Repair and Regeneration provides extensive international coverage of cellular and molecular biology, connective tissue, and biological mediator studies in the field of tissue repair and regeneration and serves a diverse audience of surgeons, plastic surgeons, dermatologists, biochemists, cell biologists, and others. Wound Repair and Regeneration is the official journal of The Wound Healing Society, The European Tissue Repair Society, The Japanese Society for Wound Healing, and The Australian Wound Management Association.
期刊最新文献
Effects of a bioengineered allogeneic cellular construct on burn-related macrophage phenotype. Digital ulcers associated with scleroderma: A major unmet medical need. Novel multi-spectral short-wave infrared imaging for assessment of human burn wound depth. Vitabiotic: An alternative approach to diabetic foot. Skin metabolism in obesity: A narrative review.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1