Affiliations: [a] Clinical Engineering Department, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| [b] Department of Anesthesiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
Correspondence:
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Corresponding author. Jianxia Miao, Department of Anesthesiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China. E-mail: jiean7245774000@163.com.
Abstract: The current application of intelligent algorithms has achieved certain applications in smart medical, but its application in the automatic grading of admitted patients is in a blank, which makes it difficult to allocate hospital resources effectively. In order to improve the efficiency and accuracy of automatic classification of patients admitted to hospital, this study builds the corresponding genetic algorithm operator based on genetic algorithm. At the same time, this paper uses the random method to generate the initial population and uses the inversion mutation operator to perform the mutation operation. In addition, this article combines image processing to automatically classify patient types and patient levels. Finally, this paper uses the data collection method to verify the model and input the data into the research model. The research shows that the model proposed in this paper has certain effects, which can realize the automatic grading of patients admitted, and can provide theoretical reference for subsequent related research.
