Multivariable Risk Modelling and Survival Analysis with Machine Learning in SARS-CoV-2 Infection

Aim: To evaluate the performance of a machine learning model based on demographic variables, blood tests, pre-existing comorbidities, and computed tomography(CT)-based radiomic features to predict critical outcome in patients with acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: We re...

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Detalles Bibliográficos
Autores principales: Ciarmiello, Andrea, Tutino, Francesca, Giovannini, Elisabetta, Milano, Amalia, Barattini, Matteo, Yosifov, Nikola, Calvi, Debora, Setti, Maurizo, Sivori, Massimiliano, Sani, Cinzia, Bastreri, Andrea, Staffiere, Raffaele, Stefanini, Teseo, Artioli, Stefania, Giovacchini, Giampiero
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672177/
https://www.ncbi.nlm.nih.gov/pubmed/38002776
http://dx.doi.org/10.3390/jcm12227164

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672177/
https://www.ncbi.nlm.nih.gov/pubmed/38002776
http://dx.doi.org/10.3390/jcm12227164

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