Fuzzy Logic and Deep learning Techniques for Covid-19 Detection

Belkis Hassani; Khelili Mohamed Akram; Kazar Okba; Slatnia Sihem; Saad Harous; Belkacem Athamena; Zina Houhamdi

doi:10.1109/ACIT57182.2022.9994125

Fuzzy Logic and Deep learning Techniques for Covid-19 Detection

Belkis Hassani, Khelili Mohamed Akram, Kazar Okba, Slatnia Sihem, Saad Harous, Belkacem Athamena, Zina Houhamdi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350320244
DOIs	https://doi.org/10.1109/ACIT57182.2022.9994125
Publication status	Published - 2022
Externally published	Yes
Event	23rd International Arab Conference on Information Technology, ACIT 2022 - Abu Dhabi, United Arab Emirates Duration: Nov 22 2022 → Nov 24 2022

Publication series

Name	Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022

Conference

Conference	23rd International Arab Conference on Information Technology, ACIT 2022
Country/Territory	United Arab Emirates
City	Abu Dhabi
Period	11/22/22 → 11/24/22

Keywords

Artificial Intelligence
CNN Fuzzy set
Covid-19
Deep Learning
Telemedicine

ASJC Scopus subject areas

Education
Computer Networks and Communications
Computer Science Applications
Information Systems
Information Systems and Management
Health Informatics

Access to Document

10.1109/ACIT57182.2022.9994125

Cite this

Hassani, B., Akram, K. M., Okba, K., Sihem, S., Harous, S., Athamena, B., & Houhamdi, Z. (2022). Fuzzy Logic and Deep learning Techniques for Covid-19 Detection. In Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022 (Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACIT57182.2022.9994125

Fuzzy Logic and Deep learning Techniques for Covid-19 Detection. / Hassani, Belkis; Akram, Khelili Mohamed; Okba, Kazar et al.

Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hassani, B, Akram, KM, Okba, K, Sihem, S, Harous, S, Athamena, B & Houhamdi, Z 2022, Fuzzy Logic and Deep learning Techniques for Covid-19 Detection. in Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022. Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022, Institute of Electrical and Electronics Engineers Inc., 23rd International Arab Conference on Information Technology, ACIT 2022, Abu Dhabi, United Arab Emirates, 11/22/22. https://doi.org/10.1109/ACIT57182.2022.9994125

Hassani B, Akram KM, Okba K, Sihem S, Harous S, Athamena B et al. Fuzzy Logic and Deep learning Techniques for Covid-19 Detection. In Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022). doi: 10.1109/ACIT57182.2022.9994125

Hassani, Belkis ; Akram, Khelili Mohamed ; Okba, Kazar et al. / Fuzzy Logic and Deep learning Techniques for Covid-19 Detection. Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings - 2022 23rd International Arab Conference on Information Technology, ACIT 2022).

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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.",

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AU - Harous, Saad

AU - Athamena, Belkacem

AU - Houhamdi, Zina

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AB - 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.

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Fuzzy Logic and Deep learning Techniques for Covid-19 Detection

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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