Data mining in predicting liver patients using classification model
Purpose This study proposes to identify potential liver patients based on the results of a liver
function test performed during a health screening to search for signs of liver disease. It is …
function test performed during a health screening to search for signs of liver disease. It is …
Novel Method for classification of Hepatitis C Using Support Vector Machine Classifier
D Sravanthi, D JenilaRani - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Aim: The aim of this study is to figure out the presence of Novel Hepatitis C Detection using
modern classifiers, and comparing the accuracy, sensitivity, specificity between SVM …
modern classifiers, and comparing the accuracy, sensitivity, specificity between SVM …
[PDF][PDF] Analysis of associative classification for prediction of HCV response to treatment
EMF El Houby - International Journal of Computer Applications, 2013 - researchgate.net
The objective of this research is the analysis of predicting the response for treatment in
patient with hepatitis C virus. The Interferon Alfa (IFN) in combination with ribavirin (RBV) is …
patient with hepatitis C virus. The Interferon Alfa (IFN) in combination with ribavirin (RBV) is …
Prediction of Liver Disease Using a Linear Regression Algorithm
D Haryadi, DMU Atmaja… - … of Informatics and …, 2023 - ejournal.akademitelkom.ac.id
[引用][C] Data Mining on Viral Hepatitis Treatment
N Soonthornphisaj - 2007 - Kasetsart University
Hepatitis C virus (HCV) prediction by machine learning techniques
Hepatitis C being as a prevalent disease in the world especially in countries like Egypt. It is
estimated that 3-4 million new cases every year, indicating as a public health problem and …
estimated that 3-4 million new cases every year, indicating as a public health problem and …
Robust technique using Novel Artificial Neural Network Classifier for detection and classification of Hepatitis C
D Sravanthi - 2023 International Conference on Artificial …, 2023 - ieeexplore.ieee.org
Aim: The objective of this review is to compare the accuracy, sensitivity, and specificity of
ANN (Artificial Neural Network) and SVM (Support Vector Machine) Classifiers in order to …
ANN (Artificial Neural Network) and SVM (Support Vector Machine) Classifiers in order to …
Hepatitis C Risk Prediction Based on Adaboost
J Yang - Highlights in Science, Engineering and Technology, 2023 - drpress.org
Hepatitis C is one of the major public health threats. The incidence of liver cirrhosis in 20
years after infection is about 20%, and the annual incidence of hepatocellular carcinoma is …
years after infection is about 20%, and the annual incidence of hepatocellular carcinoma is …
[引用][C] Comparison of Data Models for Hepatitis Diagnosis–Data Mining Technique
S Pushpalatha, J Pandya - International Journal of Advanced Research in …, 2014
[HTML][HTML] Classification accuracy of hepatitis C virus infection outcome: data mining approach
Background The dataset from genes used to predict hepatitis C virus outcome was
evaluated in a previous study using a conventional statistical methodology. Objective The …
evaluated in a previous study using a conventional statistical methodology. Objective The …