Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT.
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ABSTRACT:
SUBMITTER: Lee EH
PROVIDER: S-EPMC7846563 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT.
Lee Edward H EH Zheng Jimmy J Colak Errol E Mohammadzadeh Maryam M Houshmand Golnaz G Bevins Nicholas N Kitamura Felipe F Altinmakas Emre E Reis Eduardo Pontes EP Kim Jae-Kwang JK Klochko Chad C Han Michelle M Moradian Sadegh S Mohammadzadeh Ali A Sharifian Hashem H Hashemi Hassan H Firouznia Kavous K Ghanaati Hossien H Gity Masoumeh M Doğan Hakan H Salehinejad Hojjat H Alves Henrique H Seekins Jayne J Abdala Nitamar N Atasoy Çetin Ç Pouraliakbar Hamidreza H Maleki Majid M Wong S Simon SS Yeom Kristen W KW
NPJ digital medicine 20210129 1
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 perf ...[more]
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