COVID-19 open source data sets: a comprehensive survey

J Shuja, E Alanazi, W Alasmary, A Alashaikh - Applied Intelligence, 2021 - Springer
In December 2019, a novel virus named COVID-19 emerged in the city of Wuhan, China. In
early 2020, the COVID-19 virus spread in all continents of the world except Antarctica …

Applications of artificial intelligence in battling against covid-19: A literature review

M Tayarani - Chaos, Solitons and Fractals, 2020 - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …

Exploring automatic diagnosis of COVID-19 from crowdsourced respiratory sound data

C Brown, J Chauhan, A Grammenos, J Han… - Proceedings of the 26th …, 2020 - dl.acm.org
Audio signals generated by the human body (eg, sighs, breathing, heart, digestion, vibration
sounds) have routinely been used by clinicians as indicators to diagnose disease or assess …

A proposed sentiment analysis deep learning algorithm for analyzing COVID-19 tweets

H Kaur, SU Ahsaan, B Alankar, V Chang - Information Systems Frontiers, 2021 - Springer
With the rise in cases of COVID-19, a bizarre situation of pressure was mounted on each
country to make arrangements to control the population and utilize the available resources …

[HTML][HTML] Automatic diagnosis of COVID-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: cough, voice, and …

KK Lella, A Pja - Alexandria Engineering Journal, 2022 - Elsevier
The problem of respiratory sound classification has received good attention from the clinical
scientists and medical researcher's community in the last year to the diagnosis of COVID-19 …

A deep learning approach for sentiment analysis of COVID-19 reviews

C Singh, T Imam, S Wibowo, S Grandhi - Applied Sciences, 2022 - mdpi.com
User-generated multi-media content, such as images, text, videos, and speech, has recently
become more popular on social media sites as a means for people to share their ideas and …

Sounds of COVID-19: exploring realistic performance of audio-based digital testing

J Han, T Xia, D Spathis, E Bondareva, C Brown… - NPJ digital …, 2022 - nature.com
To identify Coronavirus disease (COVID-19) cases efficiently, affordably, and at scale, recent
work has shown how audio (including cough, breathing and voice) based approaches can …

[HTML][HTML] A study of using cough sounds and deep neural networks for the early detection of COVID-19

R Islam, E Abdel-Raheem, M Tarique - Biomedical Engineering Advances, 2022 - Elsevier
The current clinical diagnosis of COVID-19 requires person-to-person contact, needs
variable time to produce results, and is expensive. It is even inaccessible to the general …

Exploring automatic COVID-19 diagnosis via voice and symptoms from crowdsourced data

J Han, C Brown, J Chauhan… - ICASSP 2021-2021 …, 2021 - ieeexplore.ieee.org
The development of fast and accurate screening tools, which could facilitate testing and
prevent more costly clinical tests, is key to the current pandemic of COVID-19. In this context …

A systematic review on AI/ML approaches against COVID-19 outbreak

O Dogan, S Tiwari, MA Jabbar, S Guggari - Complex & Intelligent Systems, 2021 - Springer
Abstract A pandemic disease, COVID-19, has caused trouble worldwide by infecting millions
of people. The studies that apply artificial intelligence (AI) and machine learning (ML) …