使用自然语言处理来探索患者对人工智能化身的观点,用于乳腺癌患者的支持材料:调查研究研究
Eleanor Cheese1, Raouef Ahmed Bichoo2, Kartikae Grover2
1Roche Products Ltd UK, Welwyn Garden City, United Kingdom.
针对乳腺癌患者的生成人工智能 (AI) 教育视频获得了积极的反,自然语言处理 (NLP) 有效地分析了患者的评论. 虽然人工智能化身需要改进,但人工智能生成的视频为传统患者教育材料提供了具有成本效益的替代方案.
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 患者教育
背景情况:
- 了解情况的患者提高了满意度,生活质量和健康结果.
- 传统的患者信息方法 (小册子,传单) 通常是无效的.
- 生成性人工智能为高效的教育视频制作提供了潜在的解决方案.
研究的目的:
- 利用自然语言处理 (NLP) 来分析患者对人工智能生成的教育视频的反.
- 评估患者对人工智能生成的关于乳腺癌随访计划视频的反应.
主要方法:
- 调查分发给400名乳腺癌患者;分析了98个自由文本答案.
- 应用NLP技术:情绪分析,话题建模 (BERTopic),总结和TF-IDF词云.
- 评估NLP模型在从非结构化的患者反中提取见解方面的有效性.
主要成果:
- 81%的回复是积极的或中性的;负面反集中在AI化身上.
- 主题建模确定了关键主题:治疗途径,视频内容,AI化身和最小内容响应.
- 对治疗途径和视频清晰度的积极情绪;对AI化身无人性的负面情绪.
结论:
- NLP技术成功地从患者反中产生了对生成AI教育内容的洞察力.
- 生成型人工智能视频是传统患者教育的可行,具有成本效益的替代方案,尽管人工智能化身设计需要改进.
- 人工智能产生的内容应该补充,而不是取代医疗保健中的人类互动.
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