OzNet: A New Deep Learning Approach for Automated Classification of COVID-19 Computed Tomography Scans-Reference-Cited by-同舟云学术

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OzNet: A New Deep Learning Approach for Automated Classification of COVID-19 Computed Tomography Scans

Published:2023-12-01 Issue:6 Volume:11 Page:420-436
ISSN:2167-6461
Container-title:Big Data
language:en
Short-container-title:Big Data

Author:

Ozaltin Oznur¹,Yeniay Ozgur¹^ORCID,Subasi Abdulhamit²³

Affiliation:

1. Department of Statistics, Institute of Science, Hacettepe University, Ankara, Turkey.

2. Institute of Biomedicine, Faculty of Medicine, University of Turku, Turku, Finland.

3. Department of Computer Science, College of Engineering, Effat University, Jeddah, Saudi Arabia.

Publisher

Mary Ann Liebert Inc

Subject

Information Systems and Management,Computer Science Applications,Information Systems

Link

https://www.liebertpub.com/doi/pdf/10.1089/big.2022.0042

Reference59 articles.

1. Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network

2. CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection

3. Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study

4. Prediction of COVID-19 Using Genetic Deep Learning Convolutional Neural Network (GDCNN)

5. Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images

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