Machine learning in cardiovascular radiology: ESCR position statement on design requirements, quality assessment, current applications, opportunities, and challenges

ABSTRACT: Machine learning offers great opportunities to streamline and improve clinical care from the perspective of cardiac imagers, patients, and the industry and is a very active scientific research field. In light of these advances, the European Society of Cardiovascular Radiology (ESCR), a non...

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Detalles Bibliográficos
Autores principales: Weikert, Thomas, Francone, Marco, Abbara, Suhny, Baessler, Bettina, Choi, Byoung Wook, Gutberlet, Matthias, Hecht, Elizabeth M., Loewe, Christian, Mousseaux, Elie, Natale, Luigi, Nikolaou, Konstantin, Ordovas, Karen G., Peebles, Charles, Prieto, Claudia, Salgado, Rodrigo, Velthuis, Birgitta, Vliegenthart, Rozemarijn, Bremerich, Jens, Leiner, Tim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Cardiac
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128798/
https://www.ncbi.nlm.nih.gov/pubmed/33211147
http://dx.doi.org/10.1007/s00330-020-07417-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128798/
https://www.ncbi.nlm.nih.gov/pubmed/33211147
http://dx.doi.org/10.1007/s00330-020-07417-0

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