A deep learning approach for heart disease detection using a modified multiclass attention mechanism with BiLSTM

A deep learning approach for heart disease detection using a modified multiclass attention mechanism with BiLSTM

Abstract Heart disease remains the leading cause of death globally, mainly caused by delayed diagnosis and indeterminate categorization. Many of traditional ML/DL methods have limitations of misclassification, similar features, less training data, heavy computation, and noise disturbance. This study...

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Bibliographic Details
Main Authors: Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Heart disease classification
Modified multiclass attention mechanism
Deep BiLSTM
Deep learning
Adaptive bandpass filter
Online Access:https://doi.org/10.1038/s41598-025-09594-8
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https://doi.org/10.1038/s41598-025-09594-8

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