Synthetic data analysis for early detection of Alzheimer progression through machine learning algorithms.

ABSTRACT: Alzheimer's disease (AD) is a serious neurodegenerative disorder that causes incurable and irreversible neuronal loss and synaptic dysfunction. The progress of this disease is gradual and depending on the stage of its detection, only its progression can be treated, reducing the most aggressive symptoms and the speed of its neurodegenerative progress. This article proposes an early detection model for the diagnosis of AD by performing analyses in Alzheimer's progression patient datasets, provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI), including only neuropsychological assessments and making use of feature selection techniques and machine learning models. The focus of this research is to build an ensemble machine learning model capable of early detection of a patient with

SUBMITTER: Sanchez Reyna AG 

PROVIDER: S-EPMC11784714 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature