dc.contributor.author | Martin-Isla, C | |
dc.contributor.author | Campello, VM | |
dc.contributor.author | Izquierdo, C | |
dc.contributor.author | Raisi-Estabragh, Z | |
dc.contributor.author | Baessler, B | |
dc.contributor.author | Petersen, SE | |
dc.contributor.author | Lekadir, K | |
dc.date.accessioned | 2020-06-01T12:38:21Z | |
dc.date.available | 2020-01-06 | |
dc.date.available | 2020-06-01T12:38:21Z | |
dc.date.issued | 2020-01-24 | |
dc.identifier.citation | Martin-Isla C, Campello VM, Izquierdo C, Raisi-Estabragh Z, Baeßler B, Petersen SE and Lekadir K (2020) Image-Based Cardiac Diagnosis With Machine Learning: A Review. Front. Cardiovasc. Med. 7:1. doi: 10.3389/fcvm.2020.00001 | en_US |
dc.identifier.issn | 2297-055X | |
dc.identifier.other | ARTN 1 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/64515 | |
dc.description.abstract | Cardiac imaging plays an important role in the diagnosis of cardiovascular disease (CVD). Until now, its role has been limited to visual and quantitative assessment of cardiac structure and function. However, with the advent of big data and machine learning, new opportunities are emerging to build artificial intelligence tools that will directly assist the clinician in the diagnosis of CVDs. This paper presents a thorough review of recent works in this field and provide the reader with a detailed presentation of the machine learning methods that can be further exploited to enable more automated, precise and early diagnosis of most CVDs. | en_US |
dc.publisher | Frontiers Media | en_US |
dc.relation.ispartof | FRONTIERS IN CARDIOVASCULAR MEDICINE | |
dc.rights | This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | |
dc.subject | cardiovascular disease | en_US |
dc.subject | automated diagnosis | en_US |
dc.subject | cardiac imaging | en_US |
dc.subject | artificial intelligence | en_US |
dc.subject | machine learning | en_US |
dc.subject | deep learning | en_US |
dc.subject | radiomics | en_US |
dc.title | Image-Based Cardiac Diagnosis With Machine Learning: A Review | en_US |
dc.type | Article | en_US |
dc.rights.holder | © 2020 Martin-Isla, Campello, Izquierdo, Raisi-Estabragh, Baeßler, Petersen and Lekadir. | |
dc.identifier.doi | 10.3389/fcvm.2020.00001 | |
pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000512145300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.publisher-url | http://doi.org/10.3389/fcvm.2020.00001 | |
pubs.volume | 7 | en_US |
dcterms.dateAccepted | 2020-01-06 | |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |
qmul.funder | SmartHeart::Engineering and Physical Sciences Research Council | en_US |
qmul.funder | SmartHeart::Engineering and Physical Sciences Research Council | en_US |
qmul.funder | SmartHeart::Engineering and Physical Sciences Research Council | en_US |
qmul.funder | SmartHeart::Engineering and Physical Sciences Research Council | en_US |
qmul.funder | SmartHeart::Engineering and Physical Sciences Research Council | en_US |