A deep fuzzy model for diagnosis of COVID-19 from CT images-Reference-Cited by-同舟云学术

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A deep fuzzy model for diagnosis of COVID-19 from CT images

Published:2022-06 Issue: Volume:122 Page:108883
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Song Liping^ORCID,Liu Xinyu,Chen Shuqi,Liu Shuai,Liu Xiangbin,Muhammad Khan^ORCID,Bhattacharyya Siddhartha^ORCID

Publisher

Elsevier BV

Subject

Software

Reference60 articles.

1. Covid-19 coronavirus pandemic,2021

2. Overcoming the bottleneck to widespread testing: a rapid review of nucleic acid testing approaches for COVID-19 detection;Esbin;Rna,2020

3. Ct features of coronavirus disease 2019 (COVID-19) pneumonia in 62 patients in Wuhan, China;Zhou;Amer. J. Roentgenol.,2020

4. Sars-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification;Angelov;MedRxiv,2020

5. Covid-ct-dataset: a ct scan dataset about covid-19;Zhao,2020

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1. An emerging network for COVID-19 CT-scan classification using an ensemble deep transfer learning model;Acta Tropica;2024-09

2. Aggregate-aware model with bidirectional edge generation for medical image segmentation;Applied Soft Computing;2024-09

3. A systematic survey of fuzzy deep learning for uncertain medical data;Artificial Intelligence Review;2024-08-05

4. RNE-DSNet: A Re-parameterization Neighborhood Enhancement-based Dual-Stream Network for CT image recognition;Engineering Science and Technology, an International Journal;2024-08

5. A separable privacy-preserving technique based on reversible medical data hiding in plaintext encrypted images using neural network;Multimedia Tools and Applications;2024-03-14

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