… the prevalence of hepatitis C using a variety of machine learning approaches. They did this
by using data from regular, reasonably priced blood tests to find and treat those who had the …

… Successfully treating patients … machine learning techniques to create predictive mortality
models for individuals with chronic HCV infections. Methods: Data from chronic HCV patients at …

… applied different ML techniques for predicting hepatitis C. A prediction model using the artificial
… Research 11 utilized ML algorithms to detect the inflammatory severity of hepatitis C and …

… predict the severity of the Hepatitis C virus using various Machine Learning (ML) algorithms.
… In this work, different machine learning techniques were used to diagnose the severity of …

… in chronic hepatitis C and thus outperform baseline models. Machine learning methods can
capture … , yielding more accurate predictions; our models can help target costly therapies to …

… liver disease characterized by infection with the hepatitis C virus … Citation1,Citation2
Combination therapy with interferon-alfa … of the prediction models produced by the above …

… This study employed five algorithms based on machine learning to predict hepatitis C
status. This study revealed that the k-nearest neighbors (KNN) model was incredibly accurate. …

… with treatment response in hepatitis C virus patients and response to resection among
patients … and compare predictive models using conventional regression analysis and machine-…

… model, which was specifically developed for hepatitis C prediction in Jordan. … machine
learning algorithms in diagnosing chronic liver disease, with a particular emphasis on hepatitis C. …

… of hypothetical treatment policies, we utilized historical data and reinforcement learning to
… used a previously published risk prediction model [15] to measure a patient's risk over time. …