G Chaudhari, X Jiang, A Fakhry, A Han, J Xiao… - arXiv preprint arXiv …, 2020 - arxiv.org
Rapid and affordable methods of testing for COVID-19 infections are essential to reduce infection rates and prevent medical facilities from becoming overwhelmed. Current …
J Laguarta, F Hueto, B Subirana - IEEE Open Journal of …, 2020 - ieeexplore.ieee.org
Goal: We hypothesized that COVID-19 subjects, especially including asymptomatics, could be accurately discriminated only from a forced-cough cell phone recording using Artificial …
H Xue, FD Salim - Proceedings of the 27th ACM SIGKDD Conference on …, 2021 - dl.acm.org
The usage of smartphone-collected respiratory sound, trained with deep learning models, for detecting and classifying COVID-19 becomes popular recently. It removes the need for in …
In an attempt to reduce the infection rate of the COrona VIrus Disease-19 (Covid-19) countries around the world have echoed the exigency for an economical, accessible, point …
We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …
The prevalence of ubiquitous computing enables new opportunities for lung health monitoring and assessment. In the past few years, there have been extensive studies on …
KC Santosh, N Rasmussen, M Mamun… - PeerJ Computer Science, 2022 - peerj.com
For COVID-19, the need for robust, inexpensive, and accessible screening becomes critical. Even though symptoms present differently, cough is still taken as one of the primary …
A Imran, I Posokhova, HN Qureshi, U Masood… - Informatics in medicine …, 2020 - Elsevier
Background The inability to test at scale has become humanity's Achille's heel in the ongoing war against the COVID-19 pandemic. A scalable screening tool would be a game …
This research aims to analyze the performance of state-of-the-art machine learning techniques for classifying COVID-19 from cough sounds and to identify the model (s) that …