Research on Evaluation Model of Hospital Informatization Level Based on Decision Tree Algorithm | Zendy

Fenglang Wu | Zendy; Xinran Liu | Zendy; Yudan Wang | Zendy; Xiaoliang Li | Zendy; Ming Zhou | Zendy

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Research on Evaluation Model of Hospital Informatization Level Based on Decision Tree Algorithm

Author(s) -

Fenglang Wu,

Xinran Liu,

Yudan Wang,

Xiaoliang Li,

Ming Zhou

Publication year - 2022

Publication title -

security and communication networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.446

H-Index - 43

eISSN - 1939-0114

pISSN - 1939-0122

DOI - 10.1155/2022/3777474

Subject(s) - informatization , computer science , id3 algorithm , construct (python library) , decision tree , data mining , hospital information system , algorithm , decision tree model , tree (set theory) , operations research , decision tree learning , information system , incremental decision tree , mathematics , telecommunications , mathematical analysis , electrical engineering , programming language , engineering

In order to improve the weight calculation accuracy of hospital informatization level evaluation and shorten the evaluation time, a research method of hospital informatization level evaluation model based on the decision tree algorithm is proposed. Using the decision tree algorithm combining fuzzy theory and ID3, the decision tree is constructed to analyze the hospital information data. By means of questionnaire survey, expert experience, mathematical statistics, and in-depth interview, information facilities construction, information resources construction, information scientific research application, management information, and information guarantee are selected as the nodes of the decision tree to evaluate the hospital information level. Construct the structural equation model, standardize the data, extract the weight of each evaluation index, and complete the evaluation of hospital informatization level. The experimental results show that the weight calculation results of this method are basically consistent with the actual results, and the evaluation efficiency is improved.

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