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Symptom-Based COVID19 Screening Model Combined with Surveillance Information
Dohyung Lee1, Myeongchan Kim1, Hyunwoo Choo2
1Mobile Doctor Co. Ltd, South Korea.
Abstract:
As the number of cases for COVID-19 continues to grow unprecedentedly, COVID-19 screening is becoming more important. In this study, we trained machine learning models from the Israel COVID-19 dataset and compared models that used surveillance indices of COVID-19 and those that did not. The AUC scores were 0.8478±0.0037 and 0.8062±0.005 with and without surveillance information, respectively, and there was significant improvement when the surveillance information was used.
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