Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics

OBJECTIVE: To develop a two-step machine learning (ML) based model to diagnose and predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT chest radiomic features. METHODS: Three hundred CT scans (3-classes: 100 COVID-19, 100 pneumonia, and 100 healthy subjects) were en...

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Detalles Bibliográficos
Autores principales: Moradi Khaniabadi, Pegah, Bouchareb, Yassine, Al-Dhuhli, Humoud, Shiri, Isaac, Al-Kindi, Faiza, Moradi Khaniabadi, Bita, Zaidi, Habib, Rahmim, Arman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533634/
https://www.ncbi.nlm.nih.gov/pubmed/36215849
http://dx.doi.org/10.1016/j.compbiomed.2022.106165

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533634/
https://www.ncbi.nlm.nih.gov/pubmed/36215849
http://dx.doi.org/10.1016/j.compbiomed.2022.106165

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