AFCM-LSMA: New intelligent model based on Lévy slime mould algorithm and adaptive fuzzy C-means for identification of COVID-19 infection from chest X-ray images

Author:

Anter Ahmed M.,Oliva Diego,Thakare Anuradha,Zhang Zhiguo

Funder

Natural Science Foundation of Guangdong Province

Shenzhen Peacock Plan

Science and Technology Planning Project of Shenzhen Municipality

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems

Reference42 articles.

1. The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak–an update on the status;Guo;Mil. Med. Res.,2020

2. World Health Organization. Considerations for quarantine of individuals in the context of containment for coronavirus disease (COVID-19): interim guidance, 19 March 2020 (No. WHO/2019-nCoV/IHR_Quarantine/2020.2), 2020.

3. Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks;Apostolopoulos;Phys. Eng. Sci. Med.,2020

4. On the responsible use of digital data to tackle the COVID-19 pandemic;Ienca;Nat. Med.,2020

5. Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study;Randhawa;PLoS ONE,2020

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