Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City

Background: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. Methods: We performed a nested case–control analysis of 4103 adult patie...

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Detalles Bibliográficos
Autores principales: Zucker, Jason, Gomez-Simmonds, Angela, Purpura, Lawrence J., Shoucri, Sherif, LaSota, Elijah, Morley, Nicholas E., Sovic, Brit W., Castellon, Marvin A., Theodore, Deborah A., Bartram, Logan L., Miko, Benjamin A., Scherer, Matthew L., Meyers, Kathrine A., Turner, William C., Kelly, Maureen, Pavlicova, Martina, Basaraba, Cale N., Baldwin, Matthew R., Brodie, Daniel, Burkart, Kristin M., Bathon, Joan, Uhlemann, Anne-Catrin, Yin, Michael T., Castor, Delivette, Sobieszczyk, Magdalena E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397083/
https://www.ncbi.nlm.nih.gov/pubmed/34441819
http://dx.doi.org/10.3390/jcm10163523

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397083/
https://www.ncbi.nlm.nih.gov/pubmed/34441819
http://dx.doi.org/10.3390/jcm10163523

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