Deep Regression by Feature Regularization for COVID-19 Severity Prediction

Abstract

During the COVID-19 worldwide pandemic, CT scan emerged as one of the most precise tool for identification and diagnosis of affected patients. With the increase of available medical imaging, Artificial Intelligence powered methods arisen to aid the detection and classification of COVID-19 cases. In this work, we propose a methodology to automatically inspect CT scan slices assessing the related disease severity. We competed in the ICIAP2021 COVID-19 infection percentage estimation competition, and our method scored in the top-5 at both the Validation phase ranking, with MAE = 4.912%, and Testing phase ranking, with MAE = 5.020%. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.