Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion

Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion

Abstract Alzheimer’s Disease (AD) poses a significant global health challenge, necessitating early and accurate diagnosis to enable timely interventions. AD is a progressive neurodegenerative disorder that affects millions worldwide and is one of the leading causes of cognitive impairment in older a...

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Bibliographic Details
Main Authors: Arjun Kidavunil Paduvilan, Godlin Atlas Lawrence Livingston, Sampath Kumar Kuppuchamy, Rajesh Kumar Dhanaraj, Muthuvel Subramanian, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Neuroimaging
Machine learning
Alzheimer's disease (AD)
Disease detection
Classification accuracy
Recursive feature elimination
Online Access:https://doi.org/10.1186/s12911-025-03073-w
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https://doi.org/10.1186/s12911-025-03073-w

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