共享决策,改善中风患者成年人的健康相关结果
Lidia Bajenaru1, Alexandru Sorici1, Irina Georgiana Mocanu1
1Department of Computer Science, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania.
Healthcare (Basel, Switzerland)
|June 28, 2023
概括
这项研究引入了一个人工智能驱动的决策框架,以加强中风康复. 它通过将患者的偏好纳入辅助设备和应用程序的设计,以获得更好的康复结果来赋予患者权力.
科学领域:
- 神经科学是一个神经科学.
- 康复医学 康复医学 康复医学
- 人工智能的人工智能
背景情况:
- 脑卒中是全球残疾和死亡的主要原因,需要为患者护理提供先进的解决方案.
- 目前的康复策略需要在监测,预防和治疗方面进行创新.
- 阿拉梅达项目旨在开发基于人工智能的工具,用于中风患者康复.
研究的目的:
- 提出一个共享决策 (SDM) 框架,用于开发人工智能驱动的中风康复解决方案.
- 授权中风患者在使用辅助设备和应用程序方面做出明智的决定.
- 创建一个预测工具,以改善患者的治疗结果和管理与中风相关的残疾.
主要方法:
- 开发一个涉及患者,医务人员和护理人员的SDM模型 (当地社区小组 - LCG).
- 收集中风患者的数据,包括监测的健康参数和状态变量 (运动,身体,情绪,认知,睡眠).
- 使用特定的问卷来收集患者对可穿戴传感器件和应用的需求和偏好.
主要成果:
- 定义了一个监测患者数据收集旅程的方法框架.
- 确定了患者数据收集的关键方面以及中风康复的相关健康参数.
- 根据LCG反,为患者采用可穿戴传感器件和应用程序生成一般和特定指南.
结论:
- SDM框架成功地将患者的偏好集成到ALAMEDA系统设计中.
- 为使用人工智能驱动的康复技术制定了以患者为中心的指导方针.
- 该研究强调了让最终用户参与开发中风恢复辅助技术的重要性.
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