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

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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Bibliographic Details
Main Authors: Nikolaos Mittas, Fani Chatzopoulou, Konstantinos A. Kyritsis, Christos I. Papagiannopoulos, Nikoleta F. Theodoroula, Andreas S. Papazoglou, Efstratios Karagiannidis, Georgios Sofidis, Dimitrios V. Moysidis, Nikolaos Stalikas, Anna Papa, Dimitrios Chatzidimitriou, Georgios Sianos, Lefteris Angelis, Ioannis S. Vizirianakis
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-01-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
personalized (precision) medicine
coronary artery disease
machine learning
SYNTAX score
risk-stratification model
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2021.812182/full

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https://www.frontiersin.org/articles/10.3389/fcvm.2021.812182/full

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