Interpretable 2D Deep Learning for Alzheimer’s Detection from sMRI: A Lightweight Residual CNN Approach with Comprehensive Preprocessing and Stratified Data Partitioning

Neuroimaging is a promising modality for early AD detection, facilitating timely clinical intervention. This study proposes an enhanced deep learning framework that extracts critical AD biomarkers from structural MRI (sMRI) data acquired from the ADNI. Our novel CNN architecture integrates conventio...

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Bibliografische gegevens

Hoofdauteurs:	Vyshnavi Ramineni, Jun-Hyung Kim, Goo-Rak Kwon
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2026-06-01
Reeks:	Sensors
Onderwerpen:	Alzheimer’s disease (AD) convolutional neural network (CNN) structural magnetic resonance imaging Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Online toegang:	https://www.mdpi.com/1424-8220/26/13/4100
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