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A Few-Shot Learning Approach for Covid-19 Diagnosis Using Quasi-Configured Topological Spaces Cover

A Few-Shot Learning Approach for Covid-19 Diagnosis Using Quasi-Configured Topological Spaces

Journal of Artificial Intelligence and Soft Computing Research
Volume 14 (2024): Issue 1 (January 2024)
By: Hui Liu,  Chunjie Wang,  Xin Jiang and  Mohammad Khishe  
Open Access
|Dec 2023

Authors

Hui Liu

School of Mathematics and Statistics, Changchun University of Technology, Jilin, China
School of Economics and Management, Changchun University of Technology, China

Chunjie Wang

School of Mathematics and Statistics, Changchun University of Technology, Jilin, China

Xin Jiang

Department of Biochemistry, College of Basic Medical Sciences, Jilin University, China

Mohammad Khishe

m_khishe@alumni.iust.ac.ir

Department of Electrical Engineering, Imam Khomeini Marine Science University, Nowshahr, Iran
DOI: https://doi.org/10.2478/jaiscr-2024-0005
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Language: English
Page range: 77 - 95
Submitted on: Apr 14, 2023
Accepted on: Dec 13, 2023
Published on: Dec 25, 2023
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
COVID-19,
medical diagnosis,
Quasi-Configured Topological Spaces,
few-shot learning
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2023 Hui Liu, Chunjie Wang, Xin Jiang, Mohammad Khishe, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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