Severity Assessment and Progression Prediction of COVID-19 Patients Based on the LesionEncoder Framework and Chest CT

Automatic severity assessment and progression prediction can facilitate admission, triage, and referral of COVID-19 patients. This study aims to explore the potential use of lung lesion features in the management of COVID-19, based on the assumption that lesion features may carry important diagnosti...

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Autores principales:	You-Zhen Feng, Sidong Liu, Zhong-Yuan Cheng, Juan C. Quiroz, Dana Rezazadegan, Ping-Kang Chen, Qi-Ting Lin, Long Qian, Xiao-Fang Liu, Shlomo Berkovsky, Enrico Coiera, Lei Song, Xiao-Ming Qiu, Xiang-Ran Cai
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	chest CT COVID-19 severity assessment progression prediction U-Net RNN Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/cddf71bcf46b493ba6abd98058ce246a
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Severity Assessment and Progression Prediction of COVID-19 Patients Based on the LesionEncoder Framework and Chest CT

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