Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing

Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing

Abstract Stroke prediction remains a critical area of research in healthcare, aiming to enhance early intervention and patient care strategies. This study investigates the efficacy of machine learning techniques, particularly principal component analysis (PCA) and a stacking ensemble method, for pre...

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Bibliographic Details
Main Authors: Pritam Chakraborty, Anjan Bandyopadhyay, Preeti Padma Sahu, Aniket Burman, Saurav Mallik, Najah Alsubaie, Mohamed Abbas, Mohammed S. Alqahtani, Ben Othman Soufiene
Format: Article
Language:English
Published: BMC 2024-10-01
Series:BMC Bioinformatics
Subjects:
Stroke prediction
Machine learning
Principal component analysis (PCA)
Stacking ensemble
Healthcare analytics
Predictive modeling
Online Access:https://doi.org/10.1186/s12859-024-05866-8

Internet

https://doi.org/10.1186/s12859-024-05866-8

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