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Fuzzy Logic and Deep learning Techniques for Covid-19 Detection
23rd International Arab Conference on Information Technology, ACIT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2230837
ABSTRACT
With the development of ICT and its adoption in various domains, it gained remarkable intention in the healthcare sector which introduce the telemedicine term. The coronavirus pandemic has created several challenges for researchers to develop an accurate and fast detection system. In this paper, we present a new telemedicine application to predict Covid-19 using CNN and Fuzzy set techniques. The evaluation of the system indicates high performance with a 98% F1 score, 99% of recall, 98% for precision, and 97% of accuracy. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Prognostic study Language: English Journal: 23rd International Arab Conference on Information Technology, ACIT 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Prognostic study Language: English Journal: 23rd International Arab Conference on Information Technology, ACIT 2022 Year: 2022 Document Type: Article