Clinical Predictive Models for COVID-19: Systematic Study.
Journal:
Journal of medical Internet research
PMID:
32976111
Abstract
BACKGROUND: COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapid human-to-human transmission of SARS-CoV-2, many health care systems are at risk of exceeding their health care capacities, in particular in terms of SARS-CoV-2 tests, hospital and intensive care unit (ICU) beds, and mechanical ventilators. Predictive algorithms could potentially ease the strain on health care systems by identifying those who are most likely to receive a positive SARS-CoV-2 test, be hospitalized, or admitted to the ICU.
Authors
Keywords
Algorithms
Area Under Curve
Betacoronavirus
Brazil
Clinical Laboratory Techniques
Coronavirus Infections
COVID-19
COVID-19 Testing
Hospitalization
Humans
Intensive Care Units
Machine Learning
Neural Networks, Computer
Pandemics
Pneumonia, Viral
Predictive Value of Tests
Public Health Informatics
Respiration, Artificial
Retrospective Studies
ROC Curve
SARS-CoV-2
Sensitivity and Specificity