biostudies-literatureUnknown12(10)Hu X<h4>Background</h4>The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system.<h4>Methods</h4>A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations. The total CT severity score and quantitative CT features were calculated by AI pneumonia detection and evaluation system with correction by radiologists. The clinical and CT imaging features of different types were analyzed.<h4>Results</h4>It was observed that patients in the severe type group were older than the mild type gJournal of thoracic disease5336-5346https://www.ebi.ac.uk/biostudies/studies/S-EPMC7656439biostudies-literatureCT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study.PMC7656439Zheng YXu MHu XLuo HZhen ZZhang SZeng WWang JSun ZWu ZLi XZhang YCao YChen WCheng LWang XfalseCT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study.<h4>Background</h4>The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system.<h4>Methods</h4>A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations. The total CT severity score and quantitative CT features were calculated by AI pneumonia detection and evaluation system with correction by radiologists. The clinical and CT imaging features of different types were analyzed.<h4>Results</h4>It was observed that patients in the severe type group were older than the mild type g2020-01-01T00:00:00Z2020 Oct2025-04-04T23:46:38.712Z2025-04-04T23:46:38.712ZS-EPMC76564393320936710.21037/jtd-20-1584