A Review of Shockable Arrhythmia Detection of ECG Signals Using Machine and Deep Learning Techniques

Autor: Kavya Lakkakula, Karuna Yepuganti, Saritha Saladi, Prakash Allam Jaya, Patro Kiran Kumar, Sahoo Suraj Prakash, Tadeusiewicz Ryszard, Pławiak Paweł

Publikováno v: International Journal of Applied Mathematics and Computer Science, Vol 34, Iss 3, Pp 485-511 (2024)

An electrocardiogram (ECG) is an essential medical tool for analyzing the functioning of the heart. An arrhythmia is a deviation in the shape of the ECG signal from the normal sinus rhythm. Long-term arrhythmias are the primary sources of cardiac dis

Externí odkaz: https://doaj.org/article/e20835e72008442cafbb553cab1331a6

An ensemble deep learning model for medical image fusion with Siamese neural networks and VGG-19.

Autor: Allapakam, Venu¹ (AUTHOR), Karuna, Yepuganti² (AUTHOR) karuna.y@vitap.ac.in

Publikováno v: PLoS ONE. 10/23/2024, Vol. 19 Issue 10, p1-25. 25p.

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Dwarf mongoose gannet optimization algorithm-enabled deep neuro-fuzzy network for detection of shockable ventricular cardiac arrhythmias.

Autor: Kavya, Lakkakula, Karuna, Yepuganti

Publikováno v: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (Sage Publications, Ltd.); Jul2024, Vol. 238 Issue 13, p6314-6330, 17p

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