一个整合人工智能的框架,用于临床护理,并进行持续的治疗监测
Emma Chen1,2, Shvetank Prakash3, Vijay Janapa Reddi3
1Harvard John A. Paulson School of Engineering and Applied Sciences, Boston, MA, USA. yingchen@g.harvard.edu.
Nature biomedical engineering
|November 6, 2023
概括
ClinAIOps集成了持续的健康监测和人工智能,以提供个性化治疗. 这个框架允许患者,临床医生和AI开发人员进行合作,通过数据驱动的调整来改善患者的治疗结果.
科学领域:
- 临床信息学 临床信息学
- 医疗保健中的人工智能
- 数字健康数字健康
背景情况:
- 机器学习模型复杂的健康信号和治疗.
- 人工智能的临床整合需要工作流程的调整.
研究的目的:
- 介绍ClinAIOps,这是人工智能驱动的临床护理框架.
- 将持续监测与人工智能开发相结合,以改善患者管理.
主要方法:
- ClinAIOps利用了三个反循环:由患者领导的AI调整,临床医生的AI辅助监督和开发人员反.
- 适用于血压,糖尿病和帕金森病管理的框架.
主要成果:
- 允许频繁,准确的健康测量和及时的治疗调整.
- 通过现实世界的临床数据来促进协作AI开发.
结论:
- ClinAIOps为在临床工作流程中实施AI提供了一条途径.
- 通过加强监测和个性化治疗,有可能大幅改善患者的治疗结果.
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