[Objective] This paper aims to use the structural equation model to analyze the objective index data and explore the risk factors related to the disease. [Methods] Based on literature research and linear correlation analysis, this paper extracts disease risk factors. Structural Equation modeling was used to analyze these risk factors. The disease diagnosis model was constructed using the classification regression tree (CART) algorithm, and risk factors were qualitatively and quantitatively evaluated and compared using diagnostic models. [Results] Nine risk factors related to disease were discovered. After quantitative evaluation, the indicators of disease risk factors diagnosis model based on Structural Equation Modeling were at a high level, and the overall performance was better. [Limitations] The amount of experimental data is limited, and the amount of data can be expanded to conduct experiments in the future. [Conclusions] Disease risk factors based on structural equation model can improve the early diagnosis rate of disease and can assist clinical decision-making.
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