Deep Covid Detect: An International Experience on Covid-19 Lung Detection and Prognosis Using Chest Ct Publisher



Lee EH¹ ; Zheng J¹ ; Colak E² ; Mohammadzadeh M³ ; Houshmand G⁴ ; Bevins N⁵ ; Kitamura F⁶ ; Altinmakas E⁷ ; Reis EP⁸ ; Kim JK⁹ ; Klochko C⁴ ; Han M¹ ; Moradian S¹⁰ ; Mohammadzadeh A⁴ Show All Authors
Source: npj Digital Medicine Published:2021

Abstract

The Coronavirus disease 2019 (COVID-19) presents open questions in how we clinically diagnose and assess disease course. Recently, chest computed tomography (CT) has shown utility for COVID-19 diagnosis. In this study, we developed Deep COVID DeteCT (DCD), a deep learning convolutional neural network (CNN) that uses the entire chest CT volume to automatically predict COVID-19 (COVID+) from non-COVID-19 (COVID−) pneumonia and normal controls. We discuss training strategies and differences in performance across 13 international institutions and 8 countries. The inclusion of non-China sites in training significantly improved classification performance with area under the curve (AUCs) and accuracies above 0.8 on most test sites. Furthermore, using available follow-up scans, we investigate methods to track patient disease course and predict prognosis. © 2021, The Author(s).