eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19

We present an interpretable machine learning algorithm called ‘eARDS’ for predicting ARDS in an ICU population comprising COVID-19 patients, up to 12-hours before satisfying the Berlin clinical criteria. The analysis was conducted on data collected from the Intensive care units (ICU) at Emory Health...

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Detalles Bibliográficos
Autores principales: Singhal, Lakshya, Garg, Yash, Yang, Philip, Tabaie, Azade, Wong, A. Ian, Mohammed, Akram, Chinthala, Lokesh, Kadaria, Dipen, Sodhi, Amik, Holder, Andre L., Esper, Annette, Blum, James M., Davis, Robert L., Clifford, Gari D., Martin, Greg S., Kamaleswaran, Rishikesan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462682/
https://www.ncbi.nlm.nih.gov/pubmed/34559819
http://dx.doi.org/10.1371/journal.pone.0257056

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462682/
https://www.ncbi.nlm.nih.gov/pubmed/34559819
http://dx.doi.org/10.1371/journal.pone.0257056

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