Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients

OBJECTIVE: To develop prognostic models for survival (alive or deceased status) prediction of COVID-19 patients using clinical data (demographics and history, laboratory tests, visual scoring by radiologists) and lung/lesion radiomic features extracted from chest CT images. METHODS: Overall, 152 pat...

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Detalles Bibliográficos
Autores principales: Shiri, Isaac, Sorouri, Majid, Geramifar, Parham, Nazari, Mostafa, Abdollahi, Mohammad, Salimi, Yazdan, Khosravi, Bardia, Askari, Dariush, Aghaghazvini, Leila, Hajianfar, Ghasem, Kasaeian, Amir, Abdollahi, Hamid, Arabi, Hossein, Rahmim, Arman, Radmard, Amir Reza, Zaidi, Habib
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925235/
https://www.ncbi.nlm.nih.gov/pubmed/33691201
http://dx.doi.org/10.1016/j.compbiomed.2021.104304

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925235/
https://www.ncbi.nlm.nih.gov/pubmed/33691201
http://dx.doi.org/10.1016/j.compbiomed.2021.104304

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