<scp>OVASO</scp> : Integrated binary <scp>CNN</scp> models to classify <scp>COVID</scp> ‐19, pneumonia and healthy lung in X‐ray images-Reference-Cited by-同舟云学术

OVASO : Integrated binary CNN models to classify COVID ‐19, pneumonia and healthy lung in X‐ray images

Published:2022-05-09 Issue:4 Volume:32 Page:1035-1048
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Tech

Author:

Jeong Hyunsu¹,Kim Hyunwook¹,Yoon Jiwon²,Go Kyungsup³,Gwak Jeonghwan¹⁴⁵⁶^ORCID

Affiliation:

1. Department of Software Korea National University of Transportation Chungju South Korea

2. Collaborative Program in Biostatistics University of Saskatchewan Saskatoon Saskatchewan Canada

3. Department of Business and Software for Emerging Technology University of Hanyang (ERICA) Ansan South Korea

4. Department of Biomedical Engineering Korea National University of Transportation Chungju South Korea

5. Department of AI Robotics Engineering Korea National University of Transportation Chungju South Korea

6. Department of IT · Energy Convergence (BK21 FOUR), Korea National University of Transportation Chungju South Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22742

Reference67 articles.

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2. Interpreting diagnostic tests for SARS‐CoV‐2;Stanley J;JAMA,2020

3. Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment

4. Diagnostic technologies for COVID-19: a review

5. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

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