Prediction of mortality risk and duration of hospitalization of COVID-19 patients with chronic comorbidities based on machine learning algorithms.
Parastoo AmiriMahdieh MontazeriFahimeh GhasemianFatemeh AsadiSaeed NiksazFarhad SarafzadehReza KhajoueiPublished in: Digital health (2023)
The results of this study showed that the use of ML algorithms can be a good tool to predict the risk of mortality and LoS of patients with COVID-19 and chronic comorbidities based on physiological conditions, symptoms, and demographic information of patients. The Gradient boosting and MLP algorithms can quickly identify patients at risk of death or long-term hospitalization and notify physicians to do appropriate interventions.
Keyphrases
- machine learning
- deep learning
- end stage renal disease
- artificial intelligence
- ejection fraction
- big data
- coronavirus disease
- newly diagnosed
- chronic kidney disease
- primary care
- sars cov
- peritoneal dialysis
- prognostic factors
- physical activity
- type diabetes
- healthcare
- risk factors
- coronary artery disease
- respiratory syndrome coronavirus
- cardiovascular disease