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

• 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
• Institution: Universiti Malaysia Sabah

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...