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Identification of profiles associated with conversions between the Alzheimer’s disease stages, using a machine learning approach

Abstract Background The identification of factors involved in the conversion across the different Alzheimer’s disease (AD) stages is crucial to prevent or slow the disease progression. We aimed to assess the factors and their combination associated with the conversion across the AD stages, from mild...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Virginie Dauphinot, Marie Laurent, Martin Prodel, Alexandre Civet, Alexandre Vainchtock, Claire Moutet, Pierre Krolak-Salmon, Antoine Garnier-Crussard
Format: Artigo
Sprache:Inglês
Veröffentlicht: BMC 2024-07-01
Schriftenreihe:Alzheimer’s Research & Therapy
Schlagworte:
Alzheimer’s disease
Machine learning
Decision tree
Conversion
Mild cognitive impairment
Dementia
Online-Zugang:https://doi.org/10.1186/s13195-024-01533-5
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