Machine learning approaches to predict the need for intensive care unit admission among Iranian COVID-19 patients based on ICD-10: A cross-sectional study.
Zahra KarimiJaleh S MalakAmirhossein AghakhaniMohammad Sadeq NajafiHamid AriannejadHojjat ZeraatiMir S YekaninejadPublished in: Health science reports (2024)
Naïve Bayes and lightGBM demonstrated promising results in predicting ICU admission needs in COVID-19 patients. Machine learning models could help quickly identify high-risk patients upon entry and reduce mortality and morbidity among COVID-19 patients.
Keyphrases
- machine learning
- intensive care unit
- sars cov
- end stage renal disease
- emergency department
- chronic kidney disease
- ejection fraction
- artificial intelligence
- prognostic factors
- risk factors
- type diabetes
- cardiovascular events
- cardiovascular disease
- patient reported outcomes
- deep learning
- coronary artery disease
- extracorporeal membrane oxygenation