id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-291612-j7xz1qaz	Albahri, O.S.	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	2020-07-01		.txt	text/plain	10219	557	44	authors: Albahri, O.S.; Zaidan, A.A.; Albahri, A.S.; Zaidan, B.B.; Abdulkareem, K.H.; Al-qaysi, Z.T.; Alamoodi, A.H.; Aleesa, A.M.; Chyad, M.A.; Alesa, R.M.; Kim, L.C.; Lakulu, M.M.; Ibrahim, A.B.; Rashid, N.A. title: 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 Therefore, the present study aims to (i) shed light and systematically review the research efforts of emerging and new technologies of COVID-19 medical image detection based on AI approach; (ii) map related studies into coherent taxonomy and highlight the AI techniques, datasets, case studies and AI classification types used; (iii) highlight and analyse different aspects such as research gabs and future challenges with respect to evaluation and benchmarking; and (iv) propose a potential pathway solution with detailed methodology to tackle the identified research gabs and future challenges of evaluation and benchmarking of AI classification techniques used in COVID-19 medical image detection.	./cache/cord-291612-j7xz1qaz.txt	./txt/cord-291612-j7xz1qaz.txt