{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T04:16:56Z","timestamp":1778213816358,"version":"3.51.4"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100011665","name":"Deanship of Scientific Research, King Saud University for funding through Vice Deanship of Scientific Research Chairs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3063129","type":"journal-article","created":{"date-parts":[[2021,3,2]],"date-time":"2021-03-02T20:58:10Z","timestamp":1614718690000},"page":"36955-36967","source":"Crossref","is-referenced-by-count":173,"title":["CardioXNet: A Novel Lightweight Deep Learning Framework for Cardiovascular Disease Classification Using Heart Sound Recordings"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5035-2114","authenticated-orcid":false,"given":"Samiul Based","family":"Shuvo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5213-5463","authenticated-orcid":false,"given":"Shams Nafisa","family":"Ali","sequence":"additional","affiliation":[]},{"given":"Soham Irtiza","family":"Swapnil","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5343-8370","authenticated-orcid":false,"given":"Mabrook S.","family":"Al-Rakhami","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8512-9687","authenticated-orcid":false,"given":"Abdu","family":"Gumaei","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1088\/0967-3334\/37\/12\/2181"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.105940"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103800"},{"key":"ref32","first-page":"6869","article-title":"Quantized neural networks: Training neural networks with low precision weights and activations","volume":"18","author":"hubara","year":"2017","journal-title":"J Mach Learn Res"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/app9122559"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2014.2351804"},{"key":"ref36","year":"0","journal-title":"Abnormal Heart Sounds and Murmurs&#x2014;62 Rationale | Medical Council of Canada"},{"key":"ref35","author":"mason","year":"2000","journal-title":"Listening to Heart A Comprehensive Collection Heart Sounds Murmurs"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2889437"},{"key":"ref28","article-title":"A lightweight CNN model for detecting respiratory diseases from lung auscultation sounds using EMD-CWT-based hybrid scalogram","author":"shuvo","year":"2020","journal-title":"arXiv 2009 04402"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2017.2694970"},{"key":"ref29","article-title":"SwishNet: A fast convolutional neural network for speech, music and noise classification and segmentation","author":"hussain","year":"2018","journal-title":"arXiv 1812 00149"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjca.2015.06.028"},{"key":"ref1","year":"2020","journal-title":"CVD Causes One-Third of Deaths Worldwide Study Examines Global Burden of CVD From 1990 to 2015&#x2014;American College of Cardiology"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103733"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-010-9446-7"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.08.078"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103632"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/LSENS.2019.2949170"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s10439-006-9232-3"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/jemt.22998"},{"key":"ref50","article-title":"Empirical evaluation of rectified activations in convolutional network","author":"xu","year":"2015","journal-title":"arXiv 1505 00853"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/EDGE.2018.00025"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2016.01.010"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2020.08.011"},{"key":"ref40","first-page":"255","article-title":"Convolutional networks for images, speech, and time series","author":"lecun","year":"1998","journal-title":"The Handbook of Brain Theory and Neural Networks"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2970252"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2016.10.004"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2018.2870759"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.09.101"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2007.11.003"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.11.046"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"2344","DOI":"10.3390\/app8122344","article-title":"Classification of heart sound signal using multiple features","volume":"8","author":"khan","year":"2018","journal-title":"Appl Sci"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2020.105604"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2014.05.002"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3991\/ijoe.v15i11.10804"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11760-018-1261-5"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-26766-7_71"},{"key":"ref8","first-page":"8","article-title":"Cardiac auscultation: An essential clinical skill in decline","volume":"17","author":"alam","year":"2010","journal-title":"Br J Cardiol"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-96139-2_1"},{"key":"ref49","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"arXiv 1502 03167"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s13634-018-0545-9"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref45","first-page":"1700","article-title":"Recurrent continuous translation models","author":"kalchbrenner","year":"2013","journal-title":"Proc Conf Empirical Methods Natural Lang Process"},{"key":"ref48","article-title":"SqueezeNet: AlexNet-level accuracy with $50\\times$\n fewer parameters and < 0.5 MB model size","author":"iandola","year":"2016","journal-title":"arXiv 1602 07360"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-020-02218-5"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.06.040"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.2478\/v10006-012-0034-5"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2017.2721116"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09366875.pdf?arnumber=9366875","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:57:08Z","timestamp":1639771028000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9366875\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":51,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3063129","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}