Application of Intelligent Archives Management Based on Data Mining in Hospital Archives Management

Data mining belongs to knowledge discovery, which is the process of revealing implicit, unknown, and valuable information from a large amount of fuzzy application data. The potential information revealed by data mining can help decision makers adjust market strategies and reduce market risks. The information excavated must be real and not universally known, and it can be the discovery of a specific problem. Data mining algorithms mainly include the neural network method, decision tree method, genetic algorithm, rough set method, fuzzy set method, association rule method, and so on. Archives management, also known as archive work, is the general term for various business works, in which archives directly manage archive entities and archive information and provide utilization services. It is also the most basic part of national archives. Hospital archives are an important part of hospital management, and hospital archives are the accumulation of work experience and one of the important elements for building a modern hospital. Hospital archives are documents, work records, charts, audio recordings, videos, photos, and other types of documents, audio-visual materials, and physical materials, such as certificates, trophies, and medals obtained by hospitals, departments, and individuals. The purpose of this paper is to study the application of intelligent archives management based on data mining in hospital archives management, expecting to use the existing data mining technology to improve the current hospital archives management. This paper investigates the age and educational background of hospital archives management workers and explores the relationship between them and the quality of archives management. Based on the decision number algorithm, on the basis of the database, the hospital data is classified and analyzed, and the hospital file data is classified and processed through the decision number algorithm to improve the system data processing capability. The experimental results of this paper show that among the staff working in the archives management department of the hospital, 20-to-30-year-olds account for 46.2% of the total group. According to the data, the staff in the archives management department of the hospital also tends to be younger. Among the staff under the age of 30, the file pass rate was 98.3% and the failure rate was 1.7%. Among the staff over 50 years old, the file pass rate was 99.9% and the failure rate was 0.1%. According to the data, the job is related to the experience of the employee.