Ensemble Learning Based on Hybrid Deep Learning Model for Heart Disease Early Prediction.

ABSTRACT: Many epidemics have afflicted humanity throughout history, claiming many lives. It has been noted in our time that heart disease is one of the deadliest diseases that humanity has confronted in the contemporary period. The proliferation of poor habits such as smoking, overeating, and lack of physical activity has contributed to the rise in heart disease. The killing feature of heart disease, which has earned it the moniker the "silent killer," is that it frequently has no apparent signs in advance. As a result, research is required to develop a promising model for the early identification of heart disease using simple data and symptoms. The paper's aim is to propose a deep stacking ensemble model to enhance the performance of the prediction of heart disease. The proposed ensemble model int

SUBMITTER: Almulihi A 

PROVIDER: S-EPMC9777370 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature