Analysis of voice recordings features for Classification of Parkinson's Disease-Reference-Cited by-同舟云学术

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Analysis of voice recordings features for Classification of Parkinson's Disease

Published:2024-04-08 Issue: Volume: Page:531-532
ISSN:
Container-title:Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing
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Author:

Pérez-Sánchez Beatriz¹^ORCID,Sánchez-Maroño Noelia¹^ORCID,Díaz-Freire Miguel A.²^ORCID

Affiliation:

1. Faculty of Informatics, CITIC, University of A Coruna (UDC), A Coruña, Spain

2. University of A Coruna (UDC), A Coruña, Spain

Funder

National Plan for Scientific and Technical Research and Innovation of the Spanish Government

Xunta de Galicia

Consellería de Educación, Universidade e Formación Profesional of the Xunta de Galicia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3605098.3636135

Reference4 articles.

1. Deep Learning-Based Parkinson’s Disease Classification Using Vocal Feature Sets

2. Vocal Feature Extraction-Based Artificial Intelligent Model for Parkinson’s Disease Detection

3. A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform

4. Analysis of voice as an assisting tool for detection of Parkinson's disease and its subsequent clinical interpretation

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