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Assessment of New Coronary Features on Quantitative Coronary Angiographic Images With Innovative Unsupervised Artificial Adaptive Systems: A Proof-of-Concept Study

Background and Purpose: The Active Connection Matrixes (ACMs) are unsupervised artificial adaptive systems able to extract from digital images features of interest (edges, tissue differentiation, etc.) unnoticeable with conventional systems. In this proof-of-concept study, we assessed the potentiali...

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Detalles Bibliográficos
Autores principales:	Amato, Mauro, Buscema, Massimo, Massini, Giulia, Maurelli, Guido, Grossi, Enzo, Frigerio, Beatrice, Ravani, Alessio L., Sansaro, Daniela, Coggi, Daniela, Ferrari, Cristina, Bartorelli, Antonio L., Veglia, Fabrizio, Tremoli, Elena, Baldassarre, Damiano
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2021
Materias:	Cardiovascular Medicine
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551448/ https://www.ncbi.nlm.nih.gov/pubmed/34722664 http://dx.doi.org/10.3389/fcvm.2021.730626

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