Missing Risk Factor Prediction in Cardiovascular Disease Using a Blended Dataset and Optimizing Classification With a Stacking Algorithm

Missing Risk Factor Prediction in Cardiovascular Disease Using a Blended Dataset and Optimizing Classification With a Stacking Algorithm

ABSTRACT Machine learning is important in the treatment of heart disease because it is capable of analyzing large amounts of patient data, such as medical records, imaging tests, and genetic information, in order to identify patterns and predict the risk of developing heart disease. However, most ML...

Full description

Saved in:
Bibliographic Details
Main Authors: Jannatul Mauya, Saad Sahriar, Sanjida Akther, Ruhul Amin, Sabba Ruhi, Md. Shamim Reza
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Engineering Reports
Subjects:
feature ensemble
heart disease
ML algorithms
risk factors
stack classifier
Online Access:https://doi.org/10.1002/eng2.13034
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1002/eng2.13034

Similar Items