COVID-19 anomaly detection and classification method based on supervised machine learning of chest X-ray images

Author:

Hasoon Jamal N.,Fadel Ali Hussein,Hameed Rasha Subhi,Mostafa Salama A.,Khalaf Bashar Ahmed,Mohammed Mazin Abed,Nedoma Jan

Funder

VSB–Technical University of Ostrava

Publisher

Elsevier BV

Subject

General Physics and Astronomy

Reference31 articles.

1. Mathematical model of COVID-19 spread in Turkey and South Africa: theory, methods, and applications;Atangana;Advances in Difference Equations,2020

2. A. S. Al-Waisy M. Abed Mohammed S. Al-Fahdawi M. S. Maashi B. Garcia-Zapirain K. Hameed Abdulkareem et al. COVID-DeepNet: hybrid multimodal deep learning system for improving COVID-19 pneumonia detection in chest X-ray images 67 2 2021 2409 2429.

3. Hemdan, E. E. D., Shouman, M. A., & Karar, M. E. (2020). Covidx-net: A framework of deep learning classifiers to diagnose covid-19 in x-ray images.arXiv preprint arXiv:2003.11055.

4. WHO Coronavirus Disease (COVID-19) Dashboard, available online, https://covid19.who.int/?gclid=EAIaIQobChMIt- aK0_v36QIVkn4rCh2v Ew0nEAAYASAAEgKqnfD_BwE, Accessed on 10/6/2020.

5. Prediction of criticality in patients with severe Covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in Wuhan;Yan;MedRxiv.,2020

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