Gallbladder Diagnosis and Importance Analysis based on Bayesian Network
Zhiqiang Cai, Peng Guo, Shen Li, Longlong Cong, Zhi-min GENG · Atlantis Press eBooks · 2017
In recent years, diagnostic and prognostic methods of cancer have become one of the research focuses in clinical medicine with the increased risk of cancer. However, how to excavate the more information from the data, how to establish the different math model, and how to verify the diagnosis further are of great significance for doctor to improve the diagnostic accuracy and reduce the diagnostic complexity. This paper collects and teases the gallbladder cancer data from the first affiliated hospital of medical college of Xi’an Jiaotong University, China, which is used to be excavated except the known tumor markers. Then, the optimal data model is set up using some typical Bayesian networks. Finally, we improve the warning factors of tumor diagnosis from the known information by putting importance calculation method into the analysis of gallbladder diagnosis.