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基于云计算的医疗大数据与骨折患者术后护理

Medical Big Data and Postoperative Nursing of Fracture Patients Based on Cloud Computing.

机构信息

China Medical University, The Fourth Affiliated Hospital of China Medical University, Shenyang, Liaoning 110032, China.

Department of Orthopedics, Air Force Medical Center of PLA Department of Orthopedics, The Fourth Medical Sciences, Beijing 100142, China.

出版信息

Biomed Res Int. 2022 Jul 11;2022:4090235. doi: 10.1155/2022/4090235. eCollection 2022.

DOI:10.1155/2022/4090235
PMID:35860795
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9293519/
Abstract

Based on the standards for wireless sensor system identification, the sensor node identity OID identification and the management object OID identification in the SNMP MIB are merged, and a management object OID identification coding mechanism for the SNMP-based wireless sensor system is proposed to make the node management system only. The identity, attributes, and multiple entities of the target sensor node in the wireless sensor network can be identified and managed by the node management object OID. The source of abnormal medical big data generally uses two models of multidimensional data and sliding window for detection and verification. First, the sliding window can be used to detect abnormalities. The result is that under this condition, the detection rate of medical big data is more than 95%; the effect is very good, but in different dimensions, the detection rate of four-dimensional data is 2.9% higher than that of a single-dimensional one. On the basis of the ZigBee wireless network, the terminal signal transmission of fracture treatment can be realized. On this basis, combined with the actual needs of fracture treatment, it can be built with its wireless module. The wireless network has a certain basic function. The reform of the nursing system was carried out on the basis of the safety and reliability of the nursing system, the efficiency of the nursing system was improved, and timely and safe nursing services were achieved.

摘要

基于无线传感器系统标识的标准,将传感器节点标识 OID 标识和 SNMP MIB 中的管理对象 OID 标识合并,并提出了一种基于 SNMP 的无线传感器系统的管理对象 OID 编码机制,使得节点管理系统只能通过节点管理对象 OID 识别、管理无线传感器网络中目标传感器节点的标识、属性和多个实体。异常医疗大数据的来源通常使用多维数据和滑动窗口两种模型进行检测和验证。首先,滑动窗口可用于检测异常。结果表明,在这种情况下,医疗大数据的检测率超过 95%;效果非常好,但在不同维度下,四维数据的检测率比一维数据高 2.9%。在 ZigBee 无线网络的基础上,实现了骨折治疗的终端信号传输。在此基础上,结合骨折治疗的实际需要,利用其无线模块构建了具有一定基本功能的无线网络。对护理系统进行了改革,在保证护理系统安全可靠的基础上,提高了护理系统的效率,实现了及时、安全的护理服务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/78e09f01bcd1/BMRI2022-4090235.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/f0d92877ec06/BMRI2022-4090235.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/62057395b44c/BMRI2022-4090235.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/94fbea5d8f7d/BMRI2022-4090235.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/7b83d5db6710/BMRI2022-4090235.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/d14cb565504f/BMRI2022-4090235.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/78e09f01bcd1/BMRI2022-4090235.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/f0d92877ec06/BMRI2022-4090235.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/f0d22fb1f102/BMRI2022-4090235.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/62057395b44c/BMRI2022-4090235.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/94fbea5d8f7d/BMRI2022-4090235.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/7b83d5db6710/BMRI2022-4090235.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/d14cb565504f/BMRI2022-4090235.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae07/9293519/78e09f01bcd1/BMRI2022-4090235.007.jpg

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引用本文的文献

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Application of 5G network combined with AI robots in personalized nursing in China: A literature review.5G 网络与人工智能机器人在中国个性化护理中的应用:文献综述。
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