… is Egyptian Hepatitis C Virus (HCV) on which several machine learning algorithms such
as … We will also use ML algorithms to predict the fibrous classes (“cirrhosis” and “non_cirrhosis”) …

… The hepatitis C virus (HCV) is a leading cause of HCC. It causes recurring hepatic injuries
that lead to cirrhosis and chronic disturbance in the hepatic functions. Eventually, this would …

… Edeh et al. developed an ensemble learning model to predict viral hepatitis C 16 . Despite …
machine learning algorithms can extract patterns in routine blood tests to detect viral hepatitis …

… method uses an imaging technique like … through machine learning (ML) methods using an
existing dataset comprising major symptoms and medical parameters to classify the patients …

… and accurately predict treatment responses. (2) Methods: We utilized our highly sensitive
cell-free DNA (cfDNA) detection system, in combination with a machine learning algorithm, to …

… or targeted screening based on the model's predictions. We have created a Machine Learning
model which helps in predicting hepatitis C virus using Logistic Regression Algorithm. To …

… decisions about treatment and prognosis. Herein, we have developed a machine learning
(ML) model that can predict patient survival and guide treatment decisions. We obtained …

… artificial intelligence system for real-time automatic prediction of TACE response in HCC
patients based on digital subtraction angiography (DSA) videos via a deep learning approach. …

… exhibits feeble responses to conventional … via differential analysis and Weighted Gene
Co-Expression Network Analysis (WGCNA). Employing three distinct machine learning algorithms …

… Ultrasonographic data was used for building and validating deep learning … treatment
responses, we converted DL feature maps into pseudo-colored maps using Selvaraju R.’s method […