Improving Cardiovascular Disease Prediction by Integrating Imputation, Imbalance Resampling, and Feature Selection Techniques into Machine Learning Model
Abstract:Cardiovascular disease (CVD) is the leading cause of death worldwide. Primary prevention is by early prediction of the disease onset. Using laboratory data from the National Health and Nutrition Examination Survey (NHANES) in 2017-2020 timeframe (N= 7.974), we tested the ability of machine learning (ML) algorithms to classify individuals at risk. The ML models were evaluated based on their classification performances after comparing four imputation, three imbalance resampling, and three feature selection techn… Show more
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