Estimating droplet size and count distributions over a prolonged period of time following a cough in indoor environments
M Jadidi, AE Karataş… - Indoor and Built …, 2024 - journals.sagepub.com
An empirical correlation and a set of machine learning (ML) models were developed to
estimate droplet size and count distributions over an extended duration after a cough at …
estimate droplet size and count distributions over an extended duration after a cough at …
Voice features of sustained phoneme as COVID-19 biomarker
Background: The COVID-19 pandemic has resulted in enormous costs to our society.
Besides finding medicines to treat those infected by the virus, it is important to find effective …
Besides finding medicines to treat those infected by the virus, it is important to find effective …
CoughNet-V2: A scalable multimodal DNN framework for point-of-care edge devices to detect symptomatic COVID-19 cough
With the emergence of COVID-19 pandemic, new attention has been given to different
acoustic bio-markers of the respiratory disorders. Deep Neural Network (DNN) has become …
acoustic bio-markers of the respiratory disorders. Deep Neural Network (DNN) has become …
Efficient Covid-19 disease diagnosis based on cough signal processing and supervised machine learning
The spread of the coronavirus has claimed the lives of millions worldwide, which led to the
emergence of an economic and health crisis at the global level, which prompted many …
emergence of an economic and health crisis at the global level, which prompted many …
Using deep learning with large aggregated datasets for COVID-19 classification from cough
ED Haritaoglu, N Rasmussen, DCH Tan, J Xiao… - arXiv preprint arXiv …, 2022 - arxiv.org
The Covid-19 pandemic has been one of the most devastating events in recent history,
claiming the lives of more than 5 million people worldwide. Even with the worldwide …
claiming the lives of more than 5 million people worldwide. Even with the worldwide …
Development of a non-invasive Covid-19 detection framework using explainable AI and data augmentation 1
This paper investigates the potential of COVID-19 detection using cough, breathing, and
voice patterns. Speech-based features, such as MFCC, zero crossing rate, spectral centroid …
voice patterns. Speech-based features, such as MFCC, zero crossing rate, spectral centroid …
Acoustic models of Brazilian Portuguese Speech based on Neural Transformers
An acoustic model, trained on a significant amount of unlabeled data, consists of a self-
supervised learned speech representation useful for solving downstream tasks, perhaps …
supervised learned speech representation useful for solving downstream tasks, perhaps …
Developing a Multi-variate Prediction Model For COVID-19 From Crowd-sourced Respiratory Voice Data
COVID-19 has affected more than 223 countries worldwide and in the Post-COVID Era,
there is a pressing need for non-invasive, low-cost, and highly scalable solutions to detect …
there is a pressing need for non-invasive, low-cost, and highly scalable solutions to detect …
The voice of COVID19: breath and cough recording classification with temporal decision trees and random Forests
Symbolic learning is the logic-based approach to machine learning, and its mission is to
provide algorithms and methodologies to extract logical information from data and express it …
provide algorithms and methodologies to extract logical information from data and express it …
An Ensemble Machine Learning Approach for Screening Covid-19 based on Urine Parameters
B Moayedi, A Keramatfar, MH Goldani… - arXiv preprint arXiv …, 2023 - arxiv.org
The rapid spread of COVID-19 and the emergence of new variants underscore the
importance of effective screening measures. Rapid diagnosis and subsequent quarantine of …
importance of effective screening measures. Rapid diagnosis and subsequent quarantine of …