Unveiling the sound of the cognitive status: Machine Learning-based speech analysis in the Alzheimer’s disease spectrum

Abstract Background Advancement in screening tools accessible to the general population for the early detection of Alzheimer’s disease (AD) and prediction of its progression is essential for achieving timely therapeutic interventions and conducting decentralized clinical trials. This study delves in...

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Hlavní autoři:	Fernando García-Gutiérrez, Montserrat Alegret, Marta Marquié, Nathalia Muñoz, Gemma Ortega, Amanda Cano, Itziar De Rojas, Pablo García-González, Clàudia Olivé, Raquel Puerta, Ainhoa García-Sanchez, María Capdevila-Bayo, Laura Montrreal, Vanesa Pytel, Maitee Rosende-Roca, Carla Zaldua, Peru Gabirondo, Lluís Tárraga, Agustín Ruiz, Mercè Boada, Sergi Valero
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2024-02-01
Edice:	Alzheimer’s Research & Therapy
Témata:	Alzheimer’s disease Mild cognitive impairment Early diagnosis Neuropsychological tests Machine Learning Speech acoustics
On-line přístup:	https://doi.org/10.1186/s13195-024-01394-y
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