An End-to-End Integrated Clinical and CT-Based Radiomics Nomogram for Predicting Disease Severity and Need for Ventilator Support in COVID-19 Patients: A Large Multisite Retrospective Study

OBJECTIVE: The disease COVID-19 has caused a widespread global pandemic with ~3. 93 million deaths worldwide. In this work, we present three models—radiomics (M(RM)), clinical (M(CM)), and combined clinical–radiomics (M(RCM)) nomogram to predict COVID-19-positive patients who will end up needing inv...

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Detalles Bibliográficos
Autores principales: Vaidya, Pranjal, Alilou, Mehdi, Hiremath, Amogh, Gupta, Amit, Bera, Kaustav, Furin, Jennifer, Armitage, Keith, Gilkeson, Robert, Yuan, Lei, Fu, Pingfu, Lu, Cheng, Ji, Mengyao, Madabhushi, Anant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Radiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696643/
https://www.ncbi.nlm.nih.gov/pubmed/36437821
http://dx.doi.org/10.3389/fradi.2022.781536

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696643/
https://www.ncbi.nlm.nih.gov/pubmed/36437821
http://dx.doi.org/10.3389/fradi.2022.781536

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