Clinical Nursing Risk Assessment and Early Warning System based on Support Vector Machine

Abstract

Clinical nursing has many risks. In the actual evaluation of early warning, the threshold set by the system is fuzzy, which leads to too long response time when the early warning system is actually running. In response to this shortcoming, a clinical nursing based on support vector machine is designed. Risk assessment and early warning system. Design the risk evaluation signal formation hardware, combine the requirements of the early warning system, design the hardware connection circuit, use the C/S network architecture to obtain clinical care risk data, calculate the clinical care risk value, use support vector machines to set different levels of early warning thresholds, and finally Complete the design of the system. Two traditional risk assessment and early warning systems and the designed assessment and early warning system are used for experiments. The results show that the response time of the designed early warning system is the shortest.