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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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Detalhes bibliográficos
Principais autores: 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
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2021-07-01
coleção:Frontiers in Cardiovascular Medicine
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Acesso em linha:https://www.frontiersin.org/articles/10.3389/fcvm.2021.685855/full
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