| Autor: |
Dohyung, Lee, Myeongchan, Kim, Hyunwoo, Choo, Soo-Yong, Shin |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Studies in health technology and informatics. 294 |
| ISSN: |
1879-8365 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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