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Title:

Successfully implemented artificial intelligence and machine learning applications in cardiology: State-of-the-art review.

Document type:
Journal Article; Review
Author(s):
Van den Eynde, Jef; Lachmann, Mark; Laugwitz, Karl-Ludwig; Manlhiot, Cedric; Kutty, Shelby
Abstract:
The omnipresence and deep impact of artificial intelligence (AI) in today's society are undeniable. While the technology has already established itself as a powerful tool in several industries, more recently it has also started to change the practice of medicine. The aim of this review is to provide healthcare providers working in the field of cardiovascular medicine with an overview of AI and machine learning (ML) algorithms that have passed the initial tests and made it into contemporary clini...     »
Journal title abbreviation:
Trends Cardiovasc Med
Year:
2023
Journal volume:
33
Journal issue:
5
Pages contribution:
265-271
Fulltext / DOI:
doi:10.1016/j.tcm.2022.01.010
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/35101642
Print-ISSN:
1050-1738
TUM Institution:
Klinik und Poliklinik für Innere Medizin I, Kardiologie
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