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Discriminant audio properties in deep learning based respiratory insufficiency detection in Brazilian Portuguese

Authors :
Gauy, Marcelo Matheus
Berti, Larissa Cristina
Cândido Jr, Arnaldo
Neto, Augusto Camargo
Goldman, Alfredo
Levin, Anna Sara Shafferman
Martins, Marcus
de Medeiros, Beatriz Raposo
Queiroz, Marcelo
Sabino, Ester Cerdeira
Svartman, Flaviane Romani Fernandes
Finger, Marcelo
Source :
Artificial Intellingence in Medicine Proceedings 2023, page 271-275
Publication Year :
2024

Abstract

This work investigates Artificial Intelligence (AI) systems that detect respiratory insufficiency (RI) by analyzing speech audios, thus treating speech as a RI biomarker. Previous works collected RI data (P1) from COVID-19 patients during the first phase of the pandemic and trained modern AI models, such as CNNs and Transformers, which achieved $96.5\%$ accuracy, showing the feasibility of RI detection via AI. Here, we collect RI patient data (P2) with several causes besides COVID-19, aiming at extending AI-based RI detection. We also collected control data from hospital patients without RI. We show that the considered models, when trained on P1, do not generalize to P2, indicating that COVID-19 RI has features that may not be found in all RI types.<br />Comment: 5 pages, 2 figures, 1 table. Published in Artificial Intelligence in Medicine (AIME) 2023

Details

Database :
arXiv
Journal :
Artificial Intellingence in Medicine Proceedings 2023, page 271-275
Publication Type :
Report
Accession number :
edsarx.2405.17569
Document Type :
Working Paper
Full Text :
https://doi.org/10.1007/978-3-031-34344-5_32