人工智能与生成皮肤病咨询信的传统方法相美:一项试点研究比较准确性,可读性和效率
Faiq Farooq1, Hywel Cooper1, Alexa Shipman1
1Department of Dermatology, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
Clinical and experimental dermatology
|July 17, 2025
概括
像ChatGPT和Heidi这样的人工智能 (AI) 平台在生成皮肤病诊所信件的准确性和速度上明显优于传统方法. 海迪提供可靠的性能,而ChatGPT显示了更高的准确性,但可读性挑战仍然存在.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 皮肤病学临床文档 皮肤病学临床文档
背景情况:
- 创建皮肤病诊所信件的传统临床医生-秘书方法耗时,并且可能缺乏准确性.
- 新兴的人工智能 (AI) 平台提供了提高临床文档效率和准确性的潜力.
研究的目的:
- 为了比较人工智能生成 (ChatGPT,Heidi) 与传统皮肤病诊所信件的准确性,可读性和效率.
- 在模拟的临床环境中对已建立的临床医生-秘书方法进行AI平台的评估.
主要方法:
- 四个脚本化的皮肤病例被用来通过传统的 dikta / transcription,ChatGPT 和 Heidi 来生成诊所信件.
- 这些信件由高级皮肤科医生对准确性,相关性,满意度,可读性 (Flesch Reading Ease) 和时间效率进行了评估.
主要成果:
- 人工智能平台表现出比传统方法更高的精度和时间效率.
- 聊天GPT获得了最高的准确性 (92.6%) 和满意度 (4.59/5),但可读性较低;Heidi (85%准确度,4.34/5满意度) 提供了结构化,高效的输出 (27秒).
- 传统方法的准确度 (58.81%) 和满意度 (3.52/5) 最低,可读性最高 (12-15年).
结论:
- 人工智能平台显著提高了皮肤病诊所信件生成的准确性和效率.
- 由于持续的性能和可靠性,海迪为临床整合提供了一个可能更合适的选择.
- 需要进一步的研究来解决AI可读性,数据安全以及现实世界的临床工作流的影响.
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