Abstract:Objective To ensure the stability of the hospital information system, better monitor the operational status of the
information system, locate the causes of the fluctuation, and bring convenience to the operation and management of the overall
hospital network. Methods With the k-nearest neighbor algorithm, a self-learning intelligent model was constructed, which could
monitor and analyze the response delay and security events of the information system, and generate an early warning and alarm
events. Results The network equipment and security equipment of the information system were configured for prevention, and after
that the problem could be quickly determined according to the antique model without extensive manual analysis, and the event could
be accurately found and handled. Conclusion After testing in a practical environment, this model can effectively detect distributed
denial of service attacks, network loops, and concurrent data limitation, so that to provide a theoretical and practical reference for
future hospital information system stability monitoring.
王泽川,马存宁,刘玉泉,袁雪,胡欣,王杰,曹新志. 基于kNN算法的流量智能化模型在医院信息系统安全运维管理中的应用[J]. 中国医疗设备, 2021, 36(6): 132-135.
WANG Zechuan, MA Cunning, LIU Yuquan, YUAN Xue, HU Xin, WANG Jie, CAO Xinzhi. Application of Traffic Intelligent Model Based on kNN Algorithm in the Safe Operation and
Maintenance Management of Hospital Information System. China Medical Devices, 2021, 36(6): 132-135.