… machine learning techniques are used in this study for the prediction of treatment response,
… Tree, OneR, Support Vector Machine and Multi-Layer Perceptron”. Performance of used …

… the possible outcome of therapy to distinguish responders from non-responders [5]. The aim
… response could predicted accurately before using combination therapy to treat the patients.…

… ) is used to treat patients infected with HCV. The present study utilized feature selection
methods (Gini Index, Chi Squared and machine learning algorithms) and other bioinformatics …

… of hepatitis C and they may respond differently to treatment. … DM and machine learning
research which aims to predict the … Classifying patients’ dataset to predict response for treatment …

… method in staging chronic liver diseases for avoiding the … evaluate different machine learning
techniques in prediction of advanced … Methods: A prospective cohort of 39,567 patients with …

… our prediction models only on patients without antiviral treatment given that antiviral treatment,
… In addition, patients with CHC without antiviral treatment provide the most representative …

… , and to know which selected features play a key role in the prediction of Hepatitis C Virus
(HCV) by using Egyptian patient’s dataset. The highest accuracy is shown by KNN (51.06%, R) …

… virologic response could be predicted accurately before therapy in patients treated with (…
led to the development of novel techniques related to machine learning using the Artificial …

… be used as an alternative method in the prediction of Hepatitis C-related diseases. … methods.
The model in this study can be used as an alternative method in the prediction of Hepatitis C…

… predict the degree of fibrosis in chronic Hepatitis C patients with ML algorithms. The nine
ML algorithms were built based on an Egyptian cohort dataset and depended on demographic …