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 cognitive impairment to dementia, at a mild, moderate or severe stage and to identify profiles associated with earliest/latest conversion across the AD stages.

Methods

In this study conducted on the real-life MEMORA cohort data collected from January 1, 2013, and December 31, 2019, three cohorts were selected depending on the baseline neurocognitive stage from a consecutive sample of patients attending a memory center, aged between 50 and 90 years old, with a diagnosis of AD during the fo

SUBMITTER: Dauphinot V 

PROVIDER: S-EPMC11282744 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature