Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning

Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning

<b>Background:</b> Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and is the most common cause of dementia. Early diagnosis of Alzheimer’s disease is critical for better management and treatment outcomes, but it remains a challenging task due to the complex nature o...

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Bibliographic Details
Main Authors: Yogita Dubey, Aditya Bhongade, Prachi Palsodkar, Punit Fulzele
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Diagnostics
Subjects:
Alzheimer’s disease
feature selection
ensemble learning
classification
explainable AI
quantitative evaluation
Online Access:https://www.mdpi.com/2075-4418/14/24/2770
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