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Accès ouvert déclaré 2024 article

Digital voice-based biomarker for monitoring respiratory quality of life: findings from the colive voice study

5Citations signalées, ce qui n’est pas une note de qualité
1Institutions déclarées
1Pays d’affiliation déclarés

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Le résumé fourni par la source

Regular monitoring of respiratory quality of life (RQoL) is essential in respiratory healthcare, facilitating prompt diagnosis and tailored treatment for chronic respiratory diseases. Voice alterations resulting from respiratory conditions create unique audio signatures that can potentially be utilized for disease screening or monitoring. Analyzing data from 1908 participants from the Colive Voice study, which collects standardized voice recordings alongside comprehensive demographic, epidemiological, and patient-reported outcome data, we evaluated various strategies to estimate RQoL from voice, including handcrafted acoustic features, standard acoustic feature sets, and advanced deep audio embeddings derived from pretrained convolutional neural networks. We compared models using clinical features alone, voice features alone, and a combination of both. The multimodal model combining clinical and voice features demonstrated the best performance, achieving an accuracy of 70.8% and an area under the receiver operating characteristic curve (AUROC) of 0.77; an improvement of over 5% in terms of accuracy and 7% in terms of AUROC compared to model utilizing voice features alone. Incorporating vocal biomarkers significantly enhanced the predictive capacity of clinical variables across all acoustic feature types, with a net classification improvement (NRI) of up to 0.19. Our digital voice-based biomarker is capable of accurately predicting RQoL, either as an alternative to or in conjunction with clinical measures, and could be used to facilitate rapid screening and remote monitoring of respiratory health status. • Vocal biomarkers are capable of accurately predicting respiratory quality of life. • Vocal biomarkers can replace clinical measures estimated from questionnaires. • Multimodal fusion of voice and clinical data improves model performance. • The proposed approach facilitates rapid screening of respiratory health status.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Digital voice-based biomarker for monitoring respiratory quality of life: findings from the colive voice study
Date Crossref
01/10/2024
Éditeur
Elsevier BV
Type
journal-article

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Les institutions déclarées

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Les sujets associés

Voice and Speech DisordersRespiratory and Cough-Related ResearchPhonocardiography and Auscultation Techniques

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