利用病人监控视频的深度解读实现智能护理设施的跨平台电子管理

Goldis Safari, Babak Majidi, Pouria Khanzadi, M. T. Manzuri
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引用次数: 5

摘要

智能健康应用程序越来越多地用于各种医疗保健环境。深度神经网络提供了复杂环境的视觉解释能力。提供智能健康和智能护理服务的一个重要组成部分是患者监测和远程临床决策管理。本文提出了一种基于深度学习的智能医疗机构患者监测与临床决策管理系统。提议的跨平台电子管理系统是医疗商业智能框架的一部分,该框架能够帮助护理提供者提供各种警报、建议、数据分析和仪表板,以便更好地响应智能护理设施中的情况。该系统处理包括视觉信息在内的各种信息,以自动提醒医生和护理提供者患者的状态。对儿童和成人护理等场景进行了一系列模拟。仿真结果表明,所提出的框架能够为智能护理机构中的患者监测提供跨平台的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-Platform E- Management for Smart Care Facilities Using Deep Interpretation of Patient Surveillance Videos
Smart health applications are increasingly used in various healthcare environments. Deep neural networks provide the ability of visual interpretation of complex environments. An important part of providing smart health and smart care services, is patient monitoring and remote clinical decision management. In this paper a deep learning based patient monitoring and clinical decision management system for smart care facilities is proposed. The proposed cross-platform e-management system is a part of a medical business intelligence framework which is capable of helping care providers with various alerts, recommendations, data analytics and dashboards for better response to the situations in a smart care facility. The proposed system processes various information including the visual information to automatically alert the physician and care provider with the status of the patients. A series of simulations are performed for scenarios including children and adult care. The simulation results show that the proposed framework is capable of providing a cross-platform solution for patient monitoring in smart care facilities.
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