Shao Rongqiang
ABSTRACT
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.
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- Introduction of the first author: Shao Rongqiang (1977-), male, senior engineer of the Information Department of Yixing Second People's Hospital, graduate student of College of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, research fields: software development, information research, big data analysis, Artificial Intelligence.Google Scholar
- Chen Yan (1997-), female, postgraduate, School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, research fields: software development, big data analysis, Artificial Intelligence.Google Scholar
- Deng Chang (1979-), male, senior engineer, Information Department of the Fourth People's Hospital of YixingGoogle Scholar
- Corresponding author: Gong Qingyue (1972-), associate professor of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, [email protected]Google Scholar
- Contact: Shao Rongqiang, School of Artificial Intelligence and Information Technology, Nanjing University of Traditional Chinese Medicine, 138 Xianlin Avenue, Qixia District, Nanjing, 13584229786, 210046, [email protected]Google Scholar
Index Terms
- Research on promoting the application of disease prediction system based on machine learnin
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