An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems

BACKGROUND: We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalizati...

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Detalles Bibliográficos
Autores principales: Kwok, Stephen Wai Hang, Wang, Guanjin, Sohel, Ferdous, Kashani, Kianoush B., Zhu, Ye, Wang, Zhen, Antpack, Eduardo, Khandelwal, Kanika, Pagali, Sandeep R., Nanda, Sanjeev, Abdalrhim, Ahmed D., Sharma, Umesh M., Bhagra, Sumit, Dugani, Sagar, Takahashi, Paul Y., Murad, Mohammad H., Yousufuddin, Mohammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010216/
https://www.ncbi.nlm.nih.gov/pubmed/36915107
http://dx.doi.org/10.1186/s12931-023-02386-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010216/
https://www.ncbi.nlm.nih.gov/pubmed/36915107
http://dx.doi.org/10.1186/s12931-023-02386-6

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