Diagnostic Accuracy of Machine Learning Models to Identify Congenital Heart Disease: A Meta-Analysis

Background: With the dearth of trained care providers to diagnose congenital heart disease (CHD) and a surge in machine learning (ML) models, this review aims to estimate the diagnostic accuracy of such models for detecting CHD. Methods: A comprehensive literature search in the PubMed, CINAHL, Wiley...

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Detalles Bibliográficos
Autores principales: Hoodbhoy, Zahra, Jiwani, Uswa, Sattar, Saima, Salam, Rehana, Hasan, Babar, Das, Jai K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297386/
https://www.ncbi.nlm.nih.gov/pubmed/34308341
http://dx.doi.org/10.3389/frai.2021.708365

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297386/
https://www.ncbi.nlm.nih.gov/pubmed/34308341
http://dx.doi.org/10.3389/frai.2021.708365

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