BACKGROUND: Disease pathogenic factors are complicated. There is not an effective method to analyze large sample data mining, and application ability of information technology of clinical doctors needs to be improved. OBJECTIVE: Using BP algorithm of artificial neural network to analyze large sample clinical cases, in order to explore inner relations between disease pathogenic factors and diseases.METHODS: Take hypertension for example, medical data of patients with hypertension in a traditional Chinese medical hospital served as experimental data, and the influence factors of the disease were simulated with Microsoft SQL Server 2005 Analysis Services, the mining data was analyzed, and a single query was used as prediction and decision support.RESULTS AND CONCLUSION: Analysis of effect of disease pathogenic factors on disease itself based on artificial neural network with BP algorithm has good predictive effect in clinical diagnosis, which is of benefit to enhance the diagnostic efficiency of medical personnel using information technology.

Objective:In the context of building intelligent hospitals, this article aimed to establish a comprehensive scientific research integrity information management system based on the hospital′s scientific research management information system, to proactively address and prevent scientific research integrity risks.Methods:We started by analyzing the needs and challenges, and then designed a system that integrated the entire process of scientific research integrity information management into the hospital′s existing scientific research management information system. This approach ensured that integrity risks were identified and controlled throughout the hospital′s scientific research management process.Results:By incorporating scientific research integrity risk prevention and control points into the design of the scientific research management information system, we effectively mitigated risks in various scientific research activities, including submission, patent application, project application, scientific research funding, and project management.Conclusions:By building a comprehensive scientific research integrity management system that spans the entire process using the hospital's scientific research management information system, we can effectively prevent scientific research integrity risks. This approach establishes a solid foundation for the hospital's scientific research integrity as well as supports its high-quality development.