The effect of confounding data features on a deep learning algorithm to predict complete coronary occlusion in a retrospective observational setting

AIMS: Deep learning (DL) has emerged in recent years as an effective technique in automated ECG analysis. METHODS AND RESULTS: A retrospective, observational study was designed to assess the feasibility of detecting induced coronary artery occlusion in human subjects earlier than experienced cardiol...

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Detalles Bibliográficos
Autores principales: Brisk, Rob, Bond, Raymond, Finlay, Dewar, McLaughlin, James, Piadlo, Alicja, Leslie, Stephen J, Gossman, David E, Menown, Ian B, McEneaney, D J, Warren, S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707936/
https://www.ncbi.nlm.nih.gov/pubmed/36711180
http://dx.doi.org/10.1093/ehjdh/ztab002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707936/
https://www.ncbi.nlm.nih.gov/pubmed/36711180
http://dx.doi.org/10.1093/ehjdh/ztab002

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