Development of an explainable machine learning model for Alzheimer’s disease prediction using clinical and behavioural features

Development of an explainable machine learning model for Alzheimer’s disease prediction using clinical and behavioural features

This article presents a reproducible machine learning methodology for the early prediction of Alzheimer’s disease (AD) using clinical and behavioural data. A comparative analysis of multiple classification algorithms was conducted, with the Gradient Boosting classifier yielding the best performance...

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Bibliographic Details
Main Authors: Rajkumar Govindarajan, K. Thirunadanasikamani, Komal Kumar Napa, S. Sathya, J. Senthil Murugan, K. G. Chandi Priya
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:MethodsX
Subjects:
Alzheimer's disease prediction
Explainable artificial intelligence
SHAP values
Gradient boosting classifier
Streamlit web application
Online Access:http://www.sciencedirect.com/science/article/pii/S221501612500336X
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http://www.sciencedirect.com/science/article/pii/S221501612500336X

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