Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease.

ABSTRACT: Due to the aging of the global population and lifestyle changes, cardiovascular disease has become the leading cause of death worldwide, causing serious public health problems and economic pressures. Early and accurate prediction of cardiovascular disease is crucial to reducing morbidity and mortality, but traditional prediction methods often lack robustness. This study focuses on integrating swarm intelligence feature selection algorithms (including whale optimization algorithm, cuckoo search algorithm, flower pollination algorithm, Harris hawk optimization algorithm, particle swarm optimization algorithm, and genetic algorithm) with machine learning technology to improve the early diagnosis of cardiovascular disease. This study systematically evaluated the performance of each feature sel

SUBMITTER: Bai T 

PROVIDER: S-EPMC11806090 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature