Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

S. Albahri, O.; A. Zaidan, A.; S. Albahri, A.; B. Zaidan, B.; Hameed Abdulkareem, Karrar; Al-Qaysi, Z.T.; H. Alamoodi, A.; Aleesa, A.M.; Chyad, M.A.; Alesa, R.M.; Kim Lim, Chen; Modi Lakulu, Muhammad; Ibrahim, A.B.; Abdul Rashid, Nazre

doi:10.1016/j.jiph.2020.06.028

Public

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

Published in Journal of Infection and Public Health • Jul 1, 2020

Authors:

O. S. Albahri

A. A. Zaidan

A. S. Albahri

Abstract

This study presents a systematic review of artificial intelligence (AI) techniques used in the detection and classification of coronavirus disease 2019 (COVID-19) medical images in terms of evaluation and benchmarking. Five reliable databases, namely, IEEE Xplore, Web of Science, PubMed, ScienceDire...

Subject

Benchmarking

Computer science

Scopus

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