Identifying Risk Factors for Complicated Post-operative Course in Tetralogy of Fallot Using a Machine Learning Approach

Identifying Risk Factors for Complicated Post-operative Course in Tetralogy of Fallot Using a Machine Learning Approach

Introduction: Tetralogy of Fallot (TOF) repair is associated with excellent operative survival. However, a subset of patients experiences post-operative complications, which can significantly alter the early and late post-operative course. We utilized a machine learning approach to identify risk fac...

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Bibliographic Details
Main Authors: Jennifer A. Faerber, Jing Huang, Xuemei Zhang, Lihai Song, Grace DeCost, Christopher E. Mascio, Chitra Ravishankar, Michael L. O'Byrne, Maryam Y. Naim, Steven M. Kawut, Elizabeth Goldmuntz, Laura Mercer-Rosa
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
tetralogy of Fallot
cardiopulmonary bypass
global longitudinal strain imaging
outcome
congenital heart defect
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2021.685855/full

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https://www.frontiersin.org/articles/10.3389/fcvm.2021.685855/full

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