Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis

10.3389/fcvm.2024.1343210

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Main Authors:	Sazzad, Faizus, Ler, Ashlynn Ai Li, Furqan, Mohammad Shaheryar, Tan, Linus Kai Zhe, Leo, Hwa Liang, Kuntjoro, Ivandito, Tay, Edgar, Kofidis, Theo
Other Authors:	MEDICINE
Format:	Article
Published:	Frontiers Media SA 2024
Subjects:	aortic valve replacement transcatheter systematic review transcatheter aortic valve prosthesis mortality artificial intelligence machine learning
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/248610
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-248610
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spelling	sg-nus-scholar.10635-2486102024-11-15T11:22:42Z Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis Sazzad, Faizus Ler, Ashlynn Ai Li Furqan, Mohammad Shaheryar Tan, Linus Kai Zhe Leo, Hwa Liang Kuntjoro, Ivandito Tay, Edgar Kofidis, Theo MEDICINE SURGERY CANCER SCIENCE INSTITUTE OF SINGAPORE COLLEGE OF DESIGN AND ENGINEERING Dr Md Faizus Sazzad aortic valve replacement transcatheter systematic review transcatheter aortic valve prosthesis mortality artificial intelligence machine learning 10.3389/fcvm.2024.1343210 Frontiers in Cardiovascular Medicine 11 2024-06-03T08:17:29Z 2024-06-03T08:17:29Z 2024-05-31 2024-06-03T04:27:12Z Article Sazzad, Faizus, Ler, Ashlynn Ai Li, Furqan, Mohammad Shaheryar, Tan, Linus Kai Zhe, Leo, Hwa Liang, Kuntjoro, Ivandito, Tay, Edgar, Kofidis, Theo (2024-05-31). Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis. Frontiers in Cardiovascular Medicine 11. ScholarBank@NUS Repository. https://doi.org/10.3389/fcvm.2024.1343210 2297-055X https://scholarbank.nus.edu.sg/handle/10635/248610 Frontiers Media SA Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	aortic valve replacement transcatheter systematic review transcatheter aortic valve prosthesis mortality artificial intelligence machine learning
spellingShingle	aortic valve replacement transcatheter systematic review transcatheter aortic valve prosthesis mortality artificial intelligence machine learning Sazzad, Faizus Ler, Ashlynn Ai Li Furqan, Mohammad Shaheryar Tan, Linus Kai Zhe Leo, Hwa Liang Kuntjoro, Ivandito Tay, Edgar Kofidis, Theo Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
description	10.3389/fcvm.2024.1343210
author2	MEDICINE
author_facet	MEDICINE Sazzad, Faizus Ler, Ashlynn Ai Li Furqan, Mohammad Shaheryar Tan, Linus Kai Zhe Leo, Hwa Liang Kuntjoro, Ivandito Tay, Edgar Kofidis, Theo
format	Article
author	Sazzad, Faizus Ler, Ashlynn Ai Li Furqan, Mohammad Shaheryar Tan, Linus Kai Zhe Leo, Hwa Liang Kuntjoro, Ivandito Tay, Edgar Kofidis, Theo
author_sort	Sazzad, Faizus
title	Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
title_short	Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
title_full	Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
title_fullStr	Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
title_full_unstemmed	Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
title_sort	harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis
publisher	Frontiers Media SA
publishDate	2024
url	https://scholarbank.nus.edu.sg/handle/10635/248610
_version_	1821200203765514240

Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis

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