在医疗保健中整合人工智能和患者的护理经验
Oluwatosin Ogundare1,2, Tolu Owadokun3, Temitope Ogundare4
1Department of Information and Decision Sciences, California State University, San Bernardino, CA, USA. oluwatosin.ogundare@csusb.edu.
Scientific reports
|July 2, 2025
概括
医疗保健中的人工智能 (AI) 提出了挑战和机遇. 这项研究模拟了患者对人工智能集成的偏好,以最大限度地提高他们的医疗保健体验,并引入了AI亲和度评分.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 人工智能的人工智能
- 公共卫生 公共卫生
背景情况:
- 人工智能 (AI) 越来越多地融入医疗保健,影响患者护理.
- 了解患者在临床和非临床环境中对人工智能的体验至关重要.
- 人工智能可以解决和加剧现有的医疗保健问题.
研究的目的:
- 在AI集成的医疗保健系统中分析患者的担忧.
- 确定人工智能集成程度如何影响患者体验.
- 根据患者的偏好,开发一个用于优化AI集成的预测模型.
主要方法:
- 经验分析患者的担忧和经验.
- 使用机器学习 (ML) 开发数学模型.
- 利用患者数据和调查响应来预测最佳的AI整合水平 (AI亲和度).
主要成果:
- 关于人口统计学 (年龄,性别,教育) 的调查答案的描述性统计数据.
- 对人工智能整合医疗保健的态度分析.
- 统计测试对AI亲和度分数在不同组之间的分布的意义.
结论:
- 人工智能亲和度评分 (AI Affinity Score) 量化了患者对在医疗保健中整合人工智能的偏好.
- 患者人口统计学显著影响医疗保健中对AI的看法和偏好.
- 预测模型可以个性化AI集成,以增强患者体验.
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