增强人工智能模型的开发和评估,用于泌尿后科查询
Madeline K Moureau1, Berkley Davis2, Christopher X Hong2
1University of Michigan Medical School, 1540 E Medical Center Dr, Ann Arbor, MI, 48109, USA. moureau@umich.edu.
International urogynecology journal
|December 9, 2025
概括
一个新的检索增强的ChatGPT模型,使用基于证据的泌尿后科材料,与标准ChatGPT相比,显著改善了AI对患者问题的反应. 这种人工智能方法增强了患者的教育和护理.
科学领域:
- 医学中的人工智能.
- 泌尿和妇科病人的教育
- 医疗保健的自然语言处理.
背景情况:
- 标准的ChatGPT模型在专业医疗领域可能缺乏准确性和相关性.
- 尿道内科的患者教育需要可靠,基于证据的信息.
- 人工智能工具有可能改善患者的理解和参与.
研究的目的:
- 开发和评估一个检索增强的ChatGPT模型,用于泌尿和妇科病人的问题.
- 为了比较检索增强模型与标准ChatGPT的性能.
- 用专家评估来评估人工智能生成的响应质量.
主要方法:
- 使用国际泌尿科医生协会患者传单创建了一个检索增强的ChatGPT-4.0模型.
- 对标准模型和检索增强模型提出了十个常见的泌尿后科问题.
- 六名泌尿科医生使用医疗人工智能质量分析 (QAMAI) 工具评估了反应.
主要成果:
- 检索增强模型的总QAMAI得分明显高于标准模型 (p < 0.01).
- 增强型模型在所有QAMAI领域的性能都超过了标准模型,包括准确性和清晰度.
- 临床评估人员在81%的时间里更喜欢检索增强模型的响应.
结论:
- 在经过审查的患者教育材料中将人工智能接地显著提高了ChatGPT在泌尿后科的响应质量.
- 提取增强模型显示了改善患者教育和支持以患者为中心的护理的希望.
- 这种人工智能方法可以为寻求泌尿外科健康指导的患者提供更可靠和有用的信息.
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