COVID-19 Prognostic Models: A Pro-con Debate for Machine Learning vs. Traditional Statistics

The SARS-CoV-2 virus, which causes the COVID-19 pandemic, has had an unprecedented impact on healthcare requiring multidisciplinary innovation and novel thinking to minimize impact and improve outcomes. Wide-ranging disciplines have collaborated including diverse clinicians (radiology, microbiology,...

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Detalles Bibliográficos
Autores principales: Al-Hindawi, Ahmed, Abdulaal, Ahmed, Rawson, Timothy M., Alqahtani, Saleh A., Mughal, Nabeela, Moore, Luke S. P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Digital Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734592/
https://www.ncbi.nlm.nih.gov/pubmed/35005694
http://dx.doi.org/10.3389/fdgth.2021.637944

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734592/
https://www.ncbi.nlm.nih.gov/pubmed/35005694
http://dx.doi.org/10.3389/fdgth.2021.637944

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