Symptom analysis using fuzzy logic for detection and monitoring of Covid-19 patients

Symptom analysis using fuzzy logic for detection and monitoring of Covid-19 patients

Recent developments regarding the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) opened new horizons of healthcare opportunities. Moreover, these technological advancements give strength to face upcoming healthcare challenges. One of such challenges is the advent o...

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Bibliographic Details
Main Authors: Tayyaba Ilyas, Danish Mahmood, Ghufran Ahmed, Adnan Akhunzada
Format: Article
Language:English
English
Published: Multidisciplinary Digital Publishing Institute (MDPI) 2021
Subjects:
R856-857 Biomedical engineering. Electronics. Instrumentation
Online Access:https://eprints.ums.edu.my/id/eprint/33101/1/Symptom%20analysis%20using%20fuzzy%20logic%20for%20detection%20and%20monitoring%20of%20Covid-19%20patients%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33101/2/Symptom%20analysis%20using%20fuzzy%20logic%20for%20detection%20and%20monitoring%20of%20Covid-19%20patients.pdf
https://eprints.ums.edu.my/id/eprint/33101/
https://www.mdpi.com/1996-1073/14/21/7023/htm
https://doi.org/10.3390/en14217023
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Institution: Universiti Malaysia Sabah
Language: English
English

Internet

https://eprints.ums.edu.my/id/eprint/33101/1/Symptom%20analysis%20using%20fuzzy%20logic%20for%20detection%20and%20monitoring%20of%20Covid-19%20patients%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33101/2/Symptom%20analysis%20using%20fuzzy%20logic%20for%20detection%20and%20monitoring%20of%20Covid-19%20patients.pdf
https://eprints.ums.edu.my/id/eprint/33101/
https://www.mdpi.com/1996-1073/14/21/7023/htm
https://doi.org/10.3390/en14217023

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