Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
Author:
Affiliation:
1. AI Lab, Sberbank of Russia, Moscow, Russia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/4200690/9760478/09681344.pdf?arnumber=9681344
Reference58 articles.
1. Automatic diagnosis of COVID-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: Cough, voice, and breath
2. A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels
3. Very deep convolutional networks for large-scale image recognition;simonyan;Proc 3rd Int Conf Learn Representations,0
4. Towards Device-Agnostic Mobile Cough Detection with Convolutional Neural Networks
5. Techniques for cough sound analysis;saba,2018
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1. Deep learning and feature fusion-based lung sound recognition model to diagnoses the respiratory diseases;Soft Computing;2024-07-23
2. A large-scale and PCR-referenced vocal audio dataset for COVID-19;Scientific Data;2024-06-27
3. CoBrS: Cough Breath Segmentation for the Reduction of Class-Confounding Characteristics in Dataset Curation;2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2024-06-26
4. COVID-19 Detection from Cough Sounds Using XGBoost and LSTM Networks;Traitement du Signal;2024-04-30
5. One-Epoch Training with Single Test Sample in Test Time for Better Generalization of Cough-Based Covid-19 Detection Model;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
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