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Updated: Feb 13, 2026

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聊天GPT-5匹配外科医生级别评估面部提升候选人:一个试点概念验证研究
Ayman T Saeed1,2, R William F Breakey3, Daniel B Saleh4
1Plastic Surgery Department, Dr Tariq Hospital, Manama, Bahrain. aymantsaeed@gmail.com.
Aesthetic plastic surgery
|February 11, 2026
概括
聊天GPT-5在评估面部提升候选人和面部衰老严重性的照片中表现出高准确性,与整形外科医生相似. 这种人工智能工具显示出作为一个决策支持系统的潜力,用于整形外科的分拣和患者教育.
科学领域:
- 整形外科 整形外科 整形外科
- 人工智能的人工智能
- 医学成像分析 医学成像分析
背景情况:
- 多式人工智能 (AI) 越来越多地用于整形外科手术.
- 与专家相比,一般用途的人工智能仅仅从照片中评估面部衰老和面部提升候选人的能力是未知的.
研究的目的:
- 评估ChatGPT-5的识别面部衰老特征的能力,分层严重程度,并从图像中确定面部提升候选人.
- 为了比较ChatGPT-5的性能与董事会认证的整形外科医生.
主要方法:
- 一项观察性试点研究,涉及22名志愿者,他们接受了标准化面部照片.
- 五位经过董事会认证的整形外科医生和ChatGPT-5独立评估了使用相同问卷的图像.
- 统计分析包括一致性 (科恩的 κ),加权 κ,斯皮尔曼的 ρ 和平均绝对误差 (MAE).
主要成果:
- 聊天GPT-5取得了95.5%的同意与外科医生在面部整形候选人 (科恩的 κ = 0.91).
- 对二进制老化特征的共识在81.8%至90.9%之间.
- 对于顺序级严重程度,确切的同意率为77.3%,小,相邻级别的不同意见;加权的 κ 范围从0.74到0.86.
结论:
- 聊天GPT-5与仅使用标准化照片的外科医生对面部起重候选人和衰老严重性的评估密切匹配.
- 人工智能工具显示出作为分拣和患者教育的决策支持系统的希望.
- 需要进行更多的多中心研究,使用各种数据集来确认可通用性并建立部署标准.
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