人工智能聊天机器人的质量和可读性的比较,用于分拣头癌症
Taylor Kring1, Soumil Prasad1, Supriya Dadi1
1University of Miami Miller School of Medicine, Miami, FL, USA.
American journal of otolaryngology
|August 6, 2025
概括
微软Copilot在AI聊天机器人中为头癌症状查询提供了最好的质量和可读性. 从人工智能工具获得的患者信息有很大的差异,需要仔细验证准确性和可访问性.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 头癌 (HNCs) 构成了全球严重的健康负担.
- 患者越来越多地使用人工智能聊天机器人来获取健康信息,这引发了对响应质量和可读性的担忧.
研究的目的:
- 评估AI聊天机器人对头癌症状查询的响应质量和可读性.
- 为了比较领先的人工智能平台在提供患者友好的HNC信息方面的表现.
主要方法:
- 一个横截面分析评估了来自ChatGPT,Google Gemini,Microsoft Copilot和Open Evidence对25个HNC症状查询的响应.
- 修改后的DISCERN标准和SMOG评分分别用于评估响应质量和可读性.
- 为了确定统计学意义,进行了ANOVA和后期分析.
主要成果:
- 微软Copilot表现出卓越的性能,平均DISCERN得分最高 (41.40) 和平均SMOG读数水平最低 (12.56).
- 开放证据的质量最低 (平均DISCERN 30.52) 和可读性最差 (平均SMOG 17.49),表明研究生阅读水平.
- 在AI平台上观察到质量和可读性的显著差异 (p < .001).
结论:
- 对于头癌查询,人工智能生成的答案的质量和可读性存在相当大的差异.
- 特定平台的验证和监督对于确保人工智能工具提供准确和以患者为中心的信息至关重要.
- 需要进一步的研究来优化人工智能聊天机器人,以便在瘤学中可靠的患者沟通.
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