Ensembled Transfer Learning and Multiple Kernel Learning for Phonocardiogram Based Atherosclerotic Coronary Artery Disease Detection

• Published in: IEEE journal of biomedical and health informatics Vol. 26; no. 6; pp. 2804 - 2813
• Main Authors: Pathak, Akanksha, Mandana, Kayapanda, Saha, Goutam
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Arteries; Arteriosclerosis; Artificial neural networks; Atherosclerosis; Bioinformatics; Cardiovascular disease; Continuous wavelet transforms; Coronary artery; Coronary artery disease; Coronary Artery Disease - diagnostic imaging; Coronary vessels; Deep learning; Disease detection; Diseases; Heart; Heart diseases; Humans; Kernel; Kernels; Machine Learning; multiple kernel learning; Neural networks; Neural Networks, Computer; Optimization; Performance measurement; phonocardiogram; Phonocardiography; Redundancy; Transfer learning; Vein & artery diseases; VGG16

Conventional machine learning has paved the way for a simple, affordable, non-invasive approach for Coronary artery disease (CAD) detection using phonocardiogram (PCG). It leaves a scope to explore improvement of performance metrics by fusion of learned representations from deep learning. In this st...