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@article{165125,
        author = {Krushna R. Phapale and Gauri V. Mathad and Rohan S. Bedage and Rohan S. Kasliwal and Yogita S. Soma},
        title = {ECG - AI : An Intelligent System for Cardiac Health Monitoring},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {11},
        number = {1},
        pages = {452-456},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165125},
        abstract = {Electrocardiograms (ECGs), which are often analyzed by medical specialists, are essential diagnostic tools for diagnosing cardiovascular disorders. Still, there is hope for automation at the nexus of deep learning and ECG categorization. In order to provide a reliable ECG classification, this study surveys the tools, feature extraction methods, preprocessing techniques, and deep learning architectures that have been developed in this field. This study intends to provide a thorough understanding of how deep learning is transforming ECG analysis by investigating several approaches, possibly improving diagnostic precision and effectiveness in cardiovascular care.},
        keywords = {Electrocardiograms, arrhythmias, ECG classification, Feature extraction, Artificial Intelligence.},
        month = {},
        }