RDET stacking classifier: a novel machine learning based approach for stroke prediction using imbalance data.

ABSTRACT: The main cause of stroke is the unexpected blockage of blood flow to the brain. The brain cells die if blood is not supplied to them, resulting in body disability. The timely identification of medical conditions ensures patients receive the necessary treatments and assistance. This early diagnosis plays a crucial role in managing symptoms effectively and enhancing the overall quality of life for individuals affected by the stroke. The research proposed an ensemble machine learning (ML) model that predicts brain stroke while reducing parameters and computational complexity. The dataset was obtained from an open-source website Kaggle and the total number of participants is 3,254. However, this dataset needs a significant class imbalance problem. To address this issue, we utilized Synthetic M

SUBMITTER: Rehman A 

PROVIDER: S-EPMC10703010 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature