1 天前 - … , HDL_C, LDL_C, TG), smoking and alcohol consumption habits, and renal and
liver function markers. The performance of multiple machine learning models was evaluated. …

4 天前 - … with other cholestatic liver diseases. Among the six machine learning models, the
XGBoost algorithm model and RF algorithm model achieved the best predictive performance, …

7 天前 - … benefits for metabolic associated fatty liver disease (MAFLD). … of an interpretable
deep learning prediction model for … to analyze its stability and diagnostic performance in the …

11 天前 - … algorithm exhibited the best performance among the five … Based on the best-performing
predictive model, a user-… This study presented a machine learning-based predictive …

19 天前 - … This study aimed to predict PHLF using ML and compare its … In this study, we
used Pycaret to predict PHLF after liver resection for liver cancer and compared its performance …

20 天前 - … Machine learning (ML) is becoming more crucial in medical … diverse diseases such
as diabetes, heart disease, liver disease… attains improved performance over other models …

20 天前 - … AI brings to liver disease management, offering insights … demonstrate superior
performance in predicting significant … based machine learning models in predicting liver cirrhosis …

21 天前 - … predicting the stage of Liver Cirrhosis disease. A dominant trend is the use of deep
learning algorithms … Performance evaluation of various machine learning models was done …

21 天前 - … We are going discuss how to predict risk of liver disease … The aim of this study was
to examine a machine learning-… Hasan MK 2018 Performance Evaluation of Random Forests …

22 天前 - … was employed for classification, and performance was evaluated … machine learning
algorithms to enhance predictive accuracy and address gender disparities in liver disease …