A comprehensive review of analyzing the chest X-ray images to detect COVID-19 infections using deep learning techniques-Reference-Cited by-同舟云学术

A comprehensive review of analyzing the chest X-ray images to detect COVID-19 infections using deep learning techniques

Published:2023-05-27 Issue:19 Volume:27 Page:14219-14240
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Subramaniam Kavitha^ORCID,Palanisamy Natesan^ORCID,Sinnaswamy Renugadevi Ammapalayam^ORCID,Muthusamy Suresh^ORCID,Mishra Om Prava^ORCID,Loganathan Ashok Kumar^ORCID,Ramamoorthi Ponarun^ORCID,Gnanakkan Christober Asir Rajan Charles,Thangavel Gunasekaran,Sundararajan Suma Christal Mary^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-08561-7.pdf

Reference74 articles.

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2. Afshar P, Heidarian S, Naderkhani F, Oikonomou A, Plataniotis KN, Mohammadi A (2020) Covid-caps: a capsule network-based framework for identification of covid-19 cases from x-ray images. Pattern Recogn Lett 138:638–643

3. Ahmadian S, Jalali SMJ, Islam SMS, Khosravi A, Fazli E, Nahavandi S (2021) A novel deep neuroevolution-based image classification method to diagnose coronavirus disease (COVID-19). Comput Biol Med 139:104994

4. Ahsan MM, Alam TE, Trafalis T, Huebner P (2020) Deep MLP-CNN model using mixed-data to distinguish between COVID-19 and non-COVID-19 patients. Symmetry 12(9):1526

5. Alhudhaif A, Polat K, Karaman O (2021) Determination of COVID-19 pneumonia based on generalized convolutional neural network model from chest X-ray images. Expert Syst Appl 180:115141

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