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Title:

Artificial intelligence in atherosclerotic disease: Applications and trends.

Document type:
Journal Article; Review
Author(s):
Kampaktsis, Polydoros N; Emfietzoglou, Maria; Al Shehhi, Aamna; Fasoula, Nikolina-Alexia; Bakogiannis, Constantinos; Mouselimis, Dimitrios; Tsarouchas, Anastasios; Vassilikos, Vassilios P; Kallmayer, Michael; Eckstein, Hans-Henning; Hadjileontiadis, Leontios; Karlas, Angelos
Abstract:
Atherosclerotic cardiovascular disease (ASCVD) is the most common cause of death globally. Increasing amounts of highly diverse ASCVD data are becoming available and artificial intelligence (AI) techniques now bear the promise of utilizing them to improve diagnosis, advance understanding of disease pathogenesis, enable outcome prediction, assist with clinical decision making and promote precision medicine approaches. Machine learning (ML) algorithms in particular, are already employed in cardiov...     »
Journal title:
Frontiers in Cardiovascular Medicine
Journal title abbreviation:
Front Cardiovasc Med
Year:
2023
Journal volume:
9
Fulltext / DOI:
doi:10.3389/fcvm.2022.949454
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/36741834
WWW:
https://www.frontiersin.org/articles/10.3389/fcvm.2022.949454/full
TUM Institution:
Klinik und Poliklinik für Vaskuläre und Endovaskuläre Chirurgie (Prof. Eckstein); Lehrstuhl für Biologische Bildgebung - Zusammenarbeit mit dem Helmholtz-Zentrum München (Prof. Ntziachristos)
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