对领先的聊天机器人对子宫内膜异位症问题的生成人工智能反应进行比较分析
Natalie D Cohen1, Milan Ho1, Donald McIntire1
1University of Texas Southwestern, Dallas, TX (Cohen, Ho, McIntire, Smith, and Kho).
AJOG global reports
|January 15, 2025
概括
生成型人工智能 (AI) 聊天机器人提供了关于子宫内膜异位症的大部分正确但不足的答案. 随着这些大型语言模型 (LLM) 越来越多地融入患者教育中,持续评估至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 患者教育 技术 技术
背景情况:
- 生成型人工智能 (AI) 和大型语言模型 (LLM) 越来越多地被用于包括医学在内的各个行业.
- 患者可能会利用人工智能聊天机器人获取健康信息,因此需要对其准确性和全面性进行评估.
研究的目的:
- 评估三个AI聊天机器人 (ChatGPT-4,Claude,Bard) 在回答患者关于子宫内膜异位症的问题时的准确性和完整性.
- 为了确定这些聊天机器人之间响应的变化.
主要方法:
- 对ChatGPT-4,Claude和Bard提出了十个常见的子宫内膜异位症问题.
- 回答与当前的指导方针和专家意见进行了比较.
- 九名妇科医生以5分级 (不准确到全面) 评价了这些反应.
- 统计分析,包括肯德尔的W,评估了评价者之间的一致性.
主要成果:
- 平均得分是:聊天GPT-4 (4.24),克劳德 (3.70),和巴德 (3.69).
- 没有一个聊天机器人在所有问题和评论员中始终提供全面或正确的答案.
- 在关于症状和病理生理学的问题上,聊天机器人比治疗或复发风险更好.
结论:
- 人工智能聊天机器人主要提供了对子宫内膜异位症的正确但不充分的信息.
- 聊天机器人生成的内容可以补充,但不能取代医疗保健专业人员的信息.
- 对人工智能聊天机器人输出的持续评估对于准确的患者教育至关重要.
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