COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment

Author:

Bao Guoqing,Chen Huai,Liu Tongliang,Gong Guanzhong,Yin Yong,Wang Lisheng,Wang Xiuying

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference39 articles.

1. A novel coronavirus from patients with pneumonia in China, 2019;Zhu;N. Engl. J. Med.,2020

2. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China;Huang;Lancet North Am. Ed.,2020

3. Considerations in the Investigation of Cases and Clusters of COVID-19: Interim Guidance,2020

4. False-positive COVID-19 results: hidden problems and costs;Surkova;Lancet Respirat. Med.,2021

5. False negative tests for SARS-CoV-2 infection — challenges and implications;Woloshin;N. Engl. J. Med.,2020

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