Two novel nomograms for predicting the risk of hospitalization or mortality due to COVID‐19 by the naïve Bayesian classifier method

Coronavirus disease 2019 (COVID‐19) has become a global pandemic that has affected millions of people worldwide. The presence of multiple risk factors for COVID‐19 makes it difficult to plan treatment and optimize the use of medical resources. The aim of this study is to determine potential risk fac...

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Veröffentlicht in:	Journal of medical virology 2021-05, Vol.93 (5), p.3194-3201
Hauptverfasser:	Karaismailoglu, Eda, Karaismailoglu, Serkan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Aged Bayes Theorem Bayesian analysis Calibration Classifiers Coronaviruses COVID-19 COVID-19 - mortality Decision making Diabetes Diabetes mellitus Female Hospitalization Hospitalization - statistics & numerical data Humans Kidneys Male Middle Aged Mortality nomogram Nomograms Pandemics Patients Pneumonia prediction Regression analysis Renal failure Respiratory diseases Risk analysis risk factor Risk Factors SARS-CoV-2 Statistical analysis Viral diseases Virology Websites
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