Severity and Progression Quantification of COVID-19 in CT Images: a new Deep-Learning Approach-Reference-Cited by-同舟云学术

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Severity and Progression Quantification of COVID-19 in CT Images: a new Deep-Learning Approach

Published:2021-10-14 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Electrical Engineering and Photonics (EExPolytech)
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Author:

Shariaty Faridoddin^ORCID,Pavlov Vitalii,Velichko Elena,Pervunina Tatiana^ORCID,Orooji Mahdi^ORCID

Funder

INSF

RFBR

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9614688/9614689/09614774.pdf?arnumber=9614774

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Personalized Chemotherapy Selection for Lung Cancer Patients Using Machine Learning and Computed Tomography;2023 International Conference on Electrical Engineering and Photonics (EExPolytech);2023-10-19

2. Computer Vision System for Road Surface Marking Recognition;2022 International Conference on Electrical Engineering and Photonics (EExPolytech);2022-10-20

3. Development of computer-aided model to differentiate COVID-19 from pulmonary edema in lung CT scan: EDECOVID-net;Computers in Biology and Medicine;2022-02

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