Forecasting Coronary Heart Disease Risk With a 2-Step Hybrid Ensemble Learning Method and Forward Feature Selection Algorithm

Forecasting Coronary Heart Disease Risk With a 2-Step Hybrid Ensemble Learning Method and Forward Feature Selection Algorithm

Detecting cardiovascular irregularities in a timely manner is crucial for preventing any fatal risks. This research aims to devise an efficient forecasting algorithm for the timely prognosis of Coronary Heart Disease (CHD). The study includes a diverse sample of individuals from Framingham, Massachu...

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Bibliographic Details
Main Authors: Sushree Chinmayee Patra, B. Uma Maheswari, Peeta Basa Pati
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Accuracy
ensemble learning
feature weighted meta-models
F1 score
feature importance
feature optimization
Online Access:https://ieeexplore.ieee.org/document/10336765/

Internet

https://ieeexplore.ieee.org/document/10336765/

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