Abstract: Cardiovascular disease (CVD) has rapidly increased after COVID-19. Several computerized systems have been developed in the past to diagnose CVD disease. However, the high computing expenses of deep learning (DL) models and the complexity of architectures are significant issues. Therefore, to resolve these issues, an accurate diagnosis of CVD disease is required. This paper proposes a hybrid and secure deep learning (DL) system known as Heart-SecureCloud to predict multiclass heart diseases. To develop this Heart-SecureCloud system, four major stages are makeup such as preprocessing and augmentation, feature extraction and transformation, deep learning and hyperparameter optimization, and cloud security. Advanced signal processing and augmentation technologies are applied to ECG data in the preprocessing and augmentation step to enhance data quality. In the feature extraction and transformation step, adaptive wavelet transforms, and feature scaling are used to extract and convert spectral and temporal data. The DL and hyperparameter optimization step utilize a novel hybrid transformer-recurrent neural network model, which is further optimized for accuracy and efficiency using hyperband-GA. Transfer learning refines pre-trained models using domain-specific data. The unique aspect of the Heart-SecureCloud system is its implementation through a secure cloud, which safeguards medical data with encryption and access control mechanisms. The system's efficacy is demonstrated through testing and evaluation on three publicly available datasets, such as MIT-BIH Arrhythmia MIMIC-III Waveform and PTB-ECG. The Heart-SecureCloud DL architecture achieved impressive results of 98.75% of accuracy, 98.80% of recall, 98.70% of precision, and 98.75% of F1-score. Moreover, the Heart-SecureCloud DL underscores its promise for safe medical diagnostics deployment.

Talal Saad Albalawi, “Heart-SecureCloud: A Secure Cloud-Based Hybrid DL System for Diagnosis of Heart Disease Through Transformer-Recurrent Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 15(9), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150916

@article{Albalawi2024,
title = {Heart-SecureCloud: A Secure Cloud-Based Hybrid DL System for Diagnosis of Heart Disease Through Transformer-Recurrent Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150916},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150916},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {9},
author = {Talal Saad Albalawi}
}