Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning

<b>Background:</b> Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease, affecting countless individuals worldwide. PD is characterized by the onset of a marked motor symptomatology in association with several non-motor manifestations. T...

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Bibliographic Details
Main Authors:	Mehdi Rashidi, Serena Arima, Andrea Claudio Stetco, Chiara Coppola, Debora Musarò, Marco Greco, Marina Damato, Filomena My, Angela Lupo, Marta Lorenzo, Antonio Danieli, Giuseppe Maruccio, Alberto Argentiero, Andrea Buccoliero, Marcello Dorian Donzella, Michele Maffia
Format:	Article
Language:	English
Published:	MDPI AG 2025-07-01
Series:	Brain Sciences
Subjects:	Parkinson’s disease machine learning vocal features mel-frequency cepstral coefficient
Online Access:	https://www.mdpi.com/2076-3425/15/7/739
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Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning

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