Comparing machine learning classifier models in discriminating cognitively unimpaired older adults from three clinical cohorts in the Alzheimer’s disease spectrum: demonstration analyses in the COMPASS-ND study

BackgroundResearch in aging, impairment, and Alzheimer’s disease (AD) often requires powerful computational models for discriminating between clinical cohorts and identifying early biomarkers and key risk or protective factors. Machine Learning (ML) approaches represent a diverse set of data-driven...

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Principais autores:	Harrison Fah, Linzy Bohn, Russell Greiner, Roger A. Dixon
Formato:	Artigo
Idioma:	Inglês
Publicado:	Frontiers Media S.A. 2025-03-01
Series:	Frontiers in Aging Neuroscience
Assuntos:	Alzheimer’s disease Artificial Intelligence Canadian consortium on neurodegeneration in aging machine learning mild cognitive impairment eXplainable Artificial Intelligence
Acceso en liña:	https://www.frontiersin.org/articles/10.3389/fnagi.2025.1542514/full
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