Ontology highlight
ABSTRACT: Objective
The appropriate use of statins plays a vital role in reducing the risk of atherosclerotic cardiovascular disease (ASCVD). However, due to changes in diet and lifestyle, there has been a significant increase in the number of individuals with high cholesterol levels. Therefore, it is crucial to ensure the rational use of statins. Adverse reactions associated with statins, including liver enzyme abnormalities and statin-associated muscle symptoms (SAMS), have impacted their widespread utilization. In this study, we aimed to develop a predictive model for statin efficacy and safety based on real-world clinical data using machine learning techniques.Methods
We employed various data preprocessing techniques, such as improved random forest imputation and Borderline SMOTE
SUBMITTER: Xiong Y
PROVIDER: S-EPMC11317424 | biostudies-literature | 2024
REPOSITORIES: biostudies-literature