个性化数字健康的信任意识架构:整合蓝图人物和基于本体学的推理
Alina Vozna1,2, Andrea Monaldini3,4, Stefania Costantini4
1University of Pisa, Largo B. Pontecorvo, Pisa, 56127, Italy. alina.vozna@student.univaq.it.
Journal of medical systems
|October 4, 2025
概括
这项研究引入了个性化数字健康的信任意识架构,通过用户建模和自适应信任机制来增强患者护理. 它旨在改善人工智能驱动的医疗干预和用户参与.
科学领域:
- 数字健康数字健康
- 医疗保健中的人工智能
- 人与计算机的交互
背景情况:
- 个性化的数字健康解决方案需要强大的用户建模和信任机制.
- 现有的系统往往缺乏透明度和适应用户需求和信任水平的适应性.
- 整合不同的数据源 (临床,行为,环境) 对于有效的个性化至关重要.
研究的目的:
- 为个性化数字健康提供一种新的信任意识架构.
- 增强智能医疗保健代理人的用户建模和适应性信任机制.
- 促进数字健康中的透明度,用户参与和道德AI.
主要方法:
- 开发了一种基于信任的架构,结合了用户建模,符号推理和自适应信任.
- 使用蓝图人为详细的患者概况.
- 实现了基于本体论的推理层和信任的参考本体论 (ROT).
- 模拟了慢性阻塞性肺病 (COPD) 情景,用于干预交付.
主要成果:
- 该架构成功地集成了用户配置文件和实时数据,以实现个性化干预.
- 证明了系统根据不断变化的信任水平来定制通信的能力.
- 模拟干预包括药物提醒和COPD患者的空气质量警报.
结论:
- 拟议的架构为个性化数字健康提供了可扩展和模块化的方法.
- 它有助于在医疗保健中解释和伦理一致的AI系统.
- 未来的工作包括经验验证和临床平台集成.
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