Prediction of Cardiac Severity Based on ECG Images Using Deep Learning Models

With cardiovascular illnesses still posing a serious threat to world health, there is a growing demand for sophisticated diagnostic instruments that can precisely forecast the heart problems' severity. The study's main emphasis is leveraging deep learning methods for cardiac severity prediction with photos from an electrocardiogram (ECG). An extensive collection of ECG pictures covering different cardiac circumstances and degrees of severity are used to build models and assessment. CNNs, or convolutional neural networks, VGG-16, VGG-19 deep learning models are utilized to automatically retrieve detailed information from ECG pictures. Comparisons with conventional severity prediction based on ECG Convolution models are used to demonstrate and describe how the suggested deep learning method is superior. The incorporation using such Deep learning technology into medical practice has the potential to transform cardiac treatment by enabling prompt inter-ventions and enhancing the results for patients.