A New Method of Identifying the Prognostic Factors of Hepatocellular Carcinoma Patients

doi:10.23940/ijpe.23.02.p1.8593

Abstract

Abstract: Hepatocellular carcinoma (HCC) is a common malignant tumor. The prognostic of patients after operation involves many factors contributing to survival, and the long-term survival is unsatisfactory. Importance measures can be used to deal with other virtual systems to identify the critical factors influencing a result. In this paper, importance measures are used to analyze the prognostic factors influencing the survival time of HCC patients. Survival time and influencing factors are treated as systems and components to build a prognostic Bayesian network (BN) model based on a real-world data set. The importance values of factors are calculated using a BN-based importance calculation method. The sequence of factors based on importance measures is compared with the sequence obtained by Cox regression model to prove the effectiveness of importance measures in dealing with the prognostic influencing factors analysis of HCC patients.

Key words: Hepatocellular carcinoma, Cox regression, Bayesian network, importance measure

Liwei Chen, Jianhao An, Mingxin Du, and Kai Su. A New Method of Identifying the Prognostic Factors of Hepatocellular Carcinoma Patients [J]. Int J Performability Eng, 2023, 19(2): 85-93.

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