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

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

Abstract 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 hospi...

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Bibliographic Details
Main Authors: Stephen Wai Hang Kwok, Guanjin Wang, Ferdous Sohel, Kianoush B. Kashani, Ye Zhu, Zhen Wang, Eduardo Antpack, Kanika Khandelwal, Sandeep R. Pagali, Sanjeev Nanda, Ahmed D. Abdalrhim, Umesh M. Sharma, Sumit Bhagra, Sagar Dugani, Paul Y. Takahashi, Mohammad H. Murad, Mohammed Yousufuddin
Format: Article
Language:English
Published: BMC 2023-03-01
Series:Respiratory Research
Subjects:
COVID-19
Mortality
Organ failure
Prediction models
Machine learning algorithms
Online Access:https://doi.org/10.1186/s12931-023-02386-6

Internet

https://doi.org/10.1186/s12931-023-02386-6

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