Explainable artificial intelligence model for identifying COVID-19 gene biomarkers

AIM: COVID-19 has revealed the need for fast and reliable methods to assist clinicians in diagnosing the disease. This article presents a model that applies explainable artificial intelligence (XAI) methods based on machine learning techniques on COVID-19 metagenomic next-generation sequencing (mNGS...

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Detalles Bibliográficos
Autores principales: Yagin, Fatma Hilal, Cicek, İpek Balikci, Alkhateeb, Abedalrhman, Yagin, Burak, Colak, Cemil, Azzeh, Mohammad, Akbulut, Sami
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889119/
https://www.ncbi.nlm.nih.gov/pubmed/36738712
http://dx.doi.org/10.1016/j.compbiomed.2023.106619

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889119/
https://www.ncbi.nlm.nih.gov/pubmed/36738712
http://dx.doi.org/10.1016/j.compbiomed.2023.106619

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