A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: (i) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX sc...

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Detalles Bibliográficos
Autores principales: Mittas, Nikolaos, Chatzopoulou, Fani, Kyritsis, Konstantinos A., Papagiannopoulos, Christos I., Theodoroula, Nikoleta F., Papazoglou, Andreas S., Karagiannidis, Efstratios, Sofidis, Georgios, Moysidis, Dimitrios V., Stalikas, Nikolaos, Papa, Anna, Chatzidimitriou, Dimitrios, Sianos, Georgios, Angelis, Lefteris, Vizirianakis, Ioannis S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Cardiovascular Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804295/
https://www.ncbi.nlm.nih.gov/pubmed/35118145
http://dx.doi.org/10.3389/fcvm.2021.812182

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804295/
https://www.ncbi.nlm.nih.gov/pubmed/35118145
http://dx.doi.org/10.3389/fcvm.2021.812182

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