Listening for Alzheimer’s clues: machine learning analysis of multidomain speech features for cognitive impairment screening

IntroductionEarly detection of Alzheimer’s disease (AD) is critical for timely intervention, particularly during the mild cognitive impairment (MCI) stage. This study aimed to develop and evaluate a multidomain speech analysis framework to support cognitive screening, biomarker prediction within the...

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Главные авторы:	Josep Blazquez-Folch, Berta Calm, Adrián Hinojosa-Calleja, Fernando García-Gutiérrez, Montserrat Alegret, Nathalia Muñoz, Amanda Cano, Maria Victoria Fernández, Andrea Miguel, Ariadna Solivar, Itziar De Rojas, Alejandro Valenzuela-Seba, Pablo García-González, Raquel Puerta, Clàudia Olivé, Maria Capdevila-Bayo, Álvaro Muñoz-Morales, Paula Bayón-Buján, Laura Montrreal, Adelina Orellana, Gemma Ortega, Pilar Sanz-Cartagena, Maitee Rosende-Roca, Yahveth Cantero-Fortiz, Miren Jone Gurruchaga, Lluis Tarraga, Christopher Butler, Xavier Montalban, Mercè Boada, Agustín Ruiz, Marta Marquié, Sergi Valero
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Frontiers Media S.A. 2026-05-01
Серии:	Frontiers in Aging Neuroscience
Предметы:	Alzheimer’s disease cerebrospinal fluid early diagnosis machine learning mild cognitive impairment neuropsychological tests
Online-ссылка:	https://www.frontiersin.org/articles/10.3389/fnagi.2026.1816747/full
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