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A study conducted by researchers at the School of Computer Science and Engineering in Vellore, India, has developed a novel approach for detecting and classifying myocardial infarction (MI) in echocardiogram frames using an enhanced CNN algorithm and an ECV-3D network. The proposed method aims to improve the accuracy and efficiency of MI diagnosis by leveraging advanced deep learning techniques. Through extensive experimentation, the researchers achieved an accuracy of 97.05% in the detection and classification of MI, indicating the potential of their method to significantly impact the accurate diagnosis of MI and improve patient outcomes. The proposed method is also suitable for real-time clinical applications. [Extracted from the article]