Application of WeChat Public Platform Based on Big Data Analysis in Hospital Information Construction

The public platform of WeChat relies on hundreds of millions of users of WeChat, which makes it more advantaged in promotion, and gradually breaks through the limitations of traditional medical care, touching and influencing related behaviors in the medical field. This paper studies the application of WeChat public platform based on BD(big data) analysis in hospital information construction. In this paper, the architecture of medical registration system is established, and a prescription recommendation method based on ontology-based rule reasoning is proposed. The knowledge summarized by clinical knowledge base is transformed into rules, and then the rules generated based on knowledge are applied to recommendation system. By analyzing the similarity of patients' condition, diseases and symptoms with known ontology, the appropriate prescription set is selected, and the case-based reasoning model based on the similarity of patients' ontology is constructed. The results show that the accuracy of prescription recommendation algorithm based on ontology rules in this paper is improved by 8.031% compared with the traditional collaborative filtering recommendation algorithm. Compared with the single-node algorithm, it has good scalability.