预防医疗设备故障和提高患者安全的AI驱动决策支持框架:一个新的视角
Sara Awni Alkhatib1,2, Rateb Katmah1, Doua Kosaji1
1Department of Biomedical Engineering and Biotechnology, Khalifa University of Science & Technology, Abu Dhabi, United Arab Emirates.
Journal of multidisciplinary healthcare
|October 8, 2025
概括
这项研究引入了人工智能框架,用于医疗设备的预测性维护,提高患者安全和医疗保健效率. 它优先考虑以人为中心的设计和利益相关者的合作,以实现可靠的医疗器械.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 人工智能在医学中的应用
- 系统工程 系统工程
背景情况:
- 医疗设备故障严重影响患者安全和医疗保健业务.
- 当前在医疗保健维护中的人工智能应用程序是分散的,缺乏以人为中心的重点.
- 预测性维护 (PdM) 显示出潜力,但需要量身定制的医疗整合.
研究的目的:
- 为医疗设备预测性维护提出一个新的AI驱动的决策支持框架.
- 将系统思维和以人为中心的设计原则集成到医疗保健的AI中.
- 通过积极的故障预测,提高医疗器械的可靠性和安全性.
主要方法:
- 开发了一个AI框架,利用实时传感器数据和历史维护记录.
- 综合系统思维和以人为中心的设计原则.
- 整合了利益相关者的见解 (生物医学工程师,技术人员,患者,管理人员).
主要成果:
- 该框架主动预测设备故障,旨在减少停机时间.
- 强调道德和以人为中心的实施策略.
- 确定并解决了诸如数据集成和组织准备等关键挑战.
结论:
- 拟议的AI框架为更可靠的医疗设备维护提供了一条途径.
- 强调了在医疗保健中采用人工智能时,同理心,协作和安全的重要性.
- 旨在通过提高医疗器械性能和减少故障来改善患者的结果.
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