NAGNN: Classification of COVID‐19 based on neighboring aware representation from deep graph neural network-Reference-Cited by-同舟云学术

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NAGNN: Classification of COVID‐19 based on neighboring aware representation from deep graph neural network

Published:2021-09-21 Issue:2 Volume:37 Page:1572-1598
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int J of Intelligent Sys

Author:

Lu Siyuan¹^ORCID,Zhu Ziquan²^ORCID,Gorriz Juan Manuel³^ORCID,Wang Shui‐Hua⁴^ORCID,Zhang Yu‐Dong¹^ORCID

Affiliation:

1. School of Informatics University of Leicester Leicester UK

2. Science in Civil Engineering University of Florida Gainesville FL USA

3. Department of Signal Theory, Networking and Communications University of Granada Granada Spain

4. School of Mathematics and Actuarial Science University of Leicester Leicester UK

Publisher

Wiley

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.22686

Reference42 articles.

1. Can AI Help in Screening Viral and COVID-19 Pneumonia?

2. A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT

3. Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-Rays

4. Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound

5. Contrastive Cross-Site Learning With Redesigned Net for COVID-19 CT Classification

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