Research on promoting the application of disease prediction system based on machine learnin

In order to solve the problem that the disease prediction system based on machine learning has more research and less clinical application, through the analysis of the training and application process of predictive disease model, it points out that the lack of interpretability of disease prediction model and the continuous optimization of disease prediction model are the reasons affecting doctors' use of the model, and proposes that doctors should be involved in the training through business parameters to improve the interpretability of the models and the process of model training and calling should be simplified to improve the experience of the system. Finally, experiments and data analysis prove that the above measures can promote the clinical application of the disease prediction model.