Deep neural networks ensemble to detect COVID-19 from CT scans.

ABSTRACT: Research on Coronavirus Disease 2019 (COVID-19) detection methods has increased in the last months as more accurate automated toolkits are required. Recent studies show that CT scan images contain useful information to detect the COVID-19 disease. However, the scarcity of large and well balanced datasets limits the possibility of using detection approaches in real diagnostic contexts as they are unable to generalize. Indeed, the performance of these models quickly becomes inadequate when applied to samples captured in different contexts (e.g., different equipment or populations) from those used in the training phase. In this paper, a novel ensemble-based approach for more accurate COVID-19 disease detection using CT scan images is proposed. This work exploits transfer learning using pre-tr

SUBMITTER: Aversano L 

PROVIDER: S-EPMC8494191 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature