High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms

We aimed to construct a prediction model based on computed tomography (CT) radiomics features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A total of 1110 patients were studied from a publicly available dataset with 4-class severity scoring performed by a radiolog...

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Detalles Bibliográficos
Autores principales: Shiri, Isaac, Mostafaei, Shayan, Haddadi Avval, Atlas, Salimi, Yazdan, Sanaat, Amirhossein, Akhavanallaf, Azadeh, Arabi, Hossein, Rahmim, Arman, Zaidi, Habib
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437017/
https://www.ncbi.nlm.nih.gov/pubmed/36050434
http://dx.doi.org/10.1038/s41598-022-18994-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437017/
https://www.ncbi.nlm.nih.gov/pubmed/36050434
http://dx.doi.org/10.1038/s41598-022-18994-z

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