Prediction of liver cancer development risk in genotype 4 hepatitis C patients using knowledge discovery modeling
Rady, Sherine; El-Bahnasy, Khaled A.; Kamal, Sanaa M.; gameel, tasneem;
Abstract
Hepatitis C is a primary reason for the liver cancer, which is a leading cause of death. The objective of this paper is to predict the hepatitis C infection progression into cirrhosis or liver cancer. For the prediction of the disease progression, a knowledge discovery framework is proposed consisting of three phases: Preprocessing, data mining and prediction. While the preprocessing phase focuses on the discretization of the training data, the data mining phase focuses on mining patients' records using a rule based classifier built by the proposed algorithm to generate a set of unique rules. Eventually, the predictor uses the rules to predict patients' disease progression. Experimentation on 1908 chronic hepatitis C Egyptian patients with 27 extracted features collected from blood samples were used to train the model, with other 406 patients' cases for testing which showed accuracy 99.5 %.
Other data
Title | Prediction of liver cancer development risk in genotype 4 hepatitis C patients using knowledge discovery modeling | Authors | Rady, Sherine ; El-Bahnasy, Khaled A.; Kamal, Sanaa M. ; gameel, tasneem | Keywords | hepatitis C virus;prediction;hepatocellular carcinoma;knowledge discovery | Issue Date | 1-Jul-2017 | Conference | 2017 IEEE 8th International Conference on Intelligent Computing and Information Systems, ICICIS 2017 | ISBN | 9772371723 | DOI | 10.1109/INTELCIS.2017.8260080 | Scopus ID | 2-s2.0-85046967085 |
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