Efficient Pandemic Infection Detection Using Wearable Sensors and Machine Learning

Author:

Abdel-Ghani Ayah1,Abughazzah Zaineh1,Akhund Mahnoor1,Abualsaud Khalid1,Yaacoub Elias1

Affiliation:

1. Qatar University,Computer Science and Engineering Department,Doha,Qatar

Publisher

IEEE

Reference18 articles.

1. Cough sound analysis and objective correlation with spirometry and clinical diagnosis

2. Exploring automatic diagnosis of COVID-19 from crowd sourced respiratory sound data;brown;in Proceedings of the 26th ACMSIGKDD International Conference on Knowledge Discovery & Data Mining,2020

3. COVID-19 cough classification using machine learning and global smartphone recordings

4. Ai4covid-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app;imran;Informatics in Medicine Unlocked,2020

5. Rapid and accurate identifica-tion of COVID-19 infection through machine learning based on clinical available blood test results;wu;medRxiv Preprints,0

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1. Advanced Covariance Methods for IoT-Based Remote Health Monitoring;Mobile Networks and Applications;2024-09-04

2. Wearable bracelet and machine learning for remote diagnosis and pandemic infection detection;Discover Applied Sciences;2024-08-19

3. Joint Use of Vital Signs and Cough Sounds for Pandemic Detection;2024 International Telecommunications Conference (ITC-Egypt);2024-07-22

4. Computational Spirometer Using Arduino Nano Application;Advances in Bioinformatics and Biomedical Engineering;2024-04-19

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