Search
 
loader loading subjects...
cover
Symptom-Based COVID19 Screening Model Combined with Surveillance Information
Dohyung Lee, Myeongchan Kim, Hyunwoo Choo, Soo-Yong Shin
719 - 720
10.3233/SHTI220569
Research Article
Studies in Health Technology and Informatics
Volume 294: Challenges of Trustable AI and Added-Value on Health
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.

Download
Creative Commons License