A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization

IMPORTANCE: Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic. OBJECTIVES: To describe the rapid development and evaluation o...

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Detalles Bibliográficos
Autores principales: Yan, Yao, Schaffter, Thomas, Bergquist, Timothy, Yu, Thomas, Prosser, Justin, Aydin, Zafer, Jabeer, Amhar, Brugere, Ivan, Gao, Jifan, Chen, Guanhua, Causey, Jason, Yao, Yuxin, Bryson, Kevin, Long, Dustin R., Jarvik, Jeffrey G., Lee, Christoph I., Wilcox, Adam, Guinney, Justin, Mooney, Sean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506231/
https://www.ncbi.nlm.nih.gov/pubmed/34633425
http://dx.doi.org/10.1001/jamanetworkopen.2021.24946

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506231/
https://www.ncbi.nlm.nih.gov/pubmed/34633425
http://dx.doi.org/10.1001/jamanetworkopen.2021.24946

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