Medical Intelligent System and Orthopedic Clinical Nursing Based on Graph Partition Sampling Algorithm

Abstract

This study summarizes the process of graph partition sampling algorithm. Through studying, observing, and comparing many different types of graph partition sampling algorithms, this study represents the learning process sampling into three steps: sampling process, aggregation process, and the calculation process of loss function. The medical intelligence system developed in this study must provide remote audio and video connections between patients, nurses, and doctors, and requires hardware, software, and network collaboration. The hardware includes a server that keeps the medical intelligence system running. The software includes the operating system and server application software that provide the basic functions of the system. The network platform provides network bandwidth and basic configuration to achieve effective connections between different parts. At the same time, the system also defines audio and video encoding and decoding standards. Orthopedic patients are often accompanied by varying degrees of activity limitation and low self-care ability, the particularity of these patients puts forward higher requirements for orthopedic clinical care management. Orthopedic clinical nursing path is a standardized nursing management method supported by evidence-based medicine. In order to meet the requirements of the system design, the goal of the system design is to use the latest computing and network communication technology to organically “connect” the nursing staff, the nursing staff, and the hospital, so that the nursing staff can enjoy the personalized guidance specially made by the doctor at any time.