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2006.01441
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CT-based COVID-19 Triage: Deep Multitask Learning Improves Joint Identification and Severity Quantification
2 June 2020
M. Goncharov
Maxim Pisov
A. Shevtsov
B. Shirokikh
Anvar Kurmukov
I. Blokhin
V. Chernina
A. Solovev
V. Gombolevskiy
S. Morozov
Mikhail Belyaev
OOD
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Papers citing
"CT-based COVID-19 Triage: Deep Multitask Learning Improves Joint Identification and Severity Quantification"
6 / 6 papers shown
Title
Multi-task learning with cross-task consistency for improved depth estimation in colonoscopy
P. E. Chavarrias-Solano
A. Bulpitt
Venkataraman Subramanian
Sharib Ali
30
0
0
30 Nov 2023
Composite Deep Network with Feature Weighting for Improved Delineation of COVID Infection in Lung CT
Pallab Dutta
S. Mitra
16
0
0
17 Jan 2023
Full-scale Deeply Supervised Attention Network for Segmenting COVID-19 Lesions
Pallab Dutta
S. Mitra
MedIm
10
3
0
27 Oct 2022
Development of a Multi-Task Learning V-Net for Pulmonary Lobar Segmentation on Computed Tomography and Application to Diseased Lungs
M. Martell
Mitchell Chen
K. Linton-Reid
J. Posma
S. Copley
E. Aboagye
11
3
0
11 May 2021
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images
Zhenyu Tang
Wei-Ye Zhao
Xingzhi Xie
Zheng Zhong
F. Shi
Jun Liu
D. Shen
28
171
0
26 Mar 2020
Lung Infection Quantification of COVID-19 in CT Images with Deep Learning
F. Shan
Yaozong Gao
Jun Wang
Weiya Shi
N. Shi
Miaofei Han
Zhong Xue
D. Shen
Yuxin Shi
111
574
0
10 Mar 2020
1