Early Triage of COVID-19 patients exploiting Data-Driven Strategies and Machine Learning Techniques

Abstract

Coronavirus disease (COVID-19) is still affecting the world. In the pandemic situation of the novel infectious disease, early detection of COVID-19 infection and severity for febrile respiratory patients is critical for efficient management of the medical system delivery system with limited medical personnel and facilities. Thus, we propose early triage exploiting data-driven strategical methods and machine learning techniques using the data of 5,628 admitted patients provided by Korea Central Disease Control Headquarters and 50 confirmed cases in Korea University Ansan Hospital. We proved validity of our data-driven strategies with machine learning models accuracy by doing 200 experiments and find out the features that affect COVID-19 through various feature selection in each medical inspection step. As a result, Stage 5 shows the results of blood test could affect to classify critical and severe cases obtaining precision of 0.2, 0.03 higher than without blood test results. But Stage 3 without blood test results achieved the highest accuracy of 0.88 showing possibility of early triage system without blood test. In conclusion, our triage system, based on data-driven strategies and machine learning techniques, can help in early detection and triage of COVID-19 patients.

Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022

“…Classification of COVID-19 severity into triage categories has was also carried out on clinical data and laboratory tests obtained during patient examination in ED [31] and 26 blood routine indicators and several demographic features [26] using a specifically developed RF-SMA-SVM model. A novel SV-LAR model was exhibited for triage based on blood sample routine data [34], in line with other approaches exploiting blood sample test data for early triage [48] Some other studies also focused on the differential diagnosis of COVID-19 from other similar diseases or to detect patients with high risk of future lung diseases, such as a diagnostic model to aid in the early identification of suspected COVID-19 pneumonia patients [24] on admission in fever clinics. Others classified the diagnosis of the patients into three categories: COVID-19 pneumonia, non-COVID-19 pneumonia and the healthy ones [43].…”