医疗物联网:慢病智能生命体征监测
Medical Internet of Things: monitoring of intelligent vital signs in chronic diseases
背景:利用物联网、互联网技术可实现慢病患者体征数据采集,并将不同来源的数据结合起来,以便了解患者的健康状况或确定患者治疗方案。方法:本文重点描述如何利用物联网技术采集慢病患者体征数据、人工智能处理体征数据的算法、预测模型构建。结果:利用人工智能技术对慢病进行早期预警,最大限度的发现和减少慢病患者健康恶化的风险。结论:医疗物联网将为慢病患者的管理提供更好的解决方案。
Background: The Internet of things and Internet technology can be used to collect the physical signs data of patients with chronic diseases, and combine the data from different sources, so as to understand the health status of patients or determine the treatment plan of patients. Methods: This paper mainly describes how to collect the physical sign data of chronic disease patients by using Internet of things technology, the algorithm of artificial intelligence processing physical sign data, and the construction of prediction model. Results: Artificial intelligence technology was used to give early warning of chronic disease, and to find and reduce the risk of health deterioration of chronic disease patients to the maximum extent. Conclusion: Medical iot will provide a better solution for the management of chronic patients.
曾红武、戴书球
医药卫生理论医学研究方法电子技术应用
慢病医疗物联网早期预警人工智能。
Slow diseaseMedical Internet of thingsEarly warningI.
曾红武,戴书球.医疗物联网:慢病智能生命体征监测[EB/OL].(2022-03-15)[2025-08-18].https://www.biomedrxiv.org.cn/article/doi/bmr.202206.00008.点此复制
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