c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer’s disease

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer’s disease

Abstract Background Alzheimer’s disease (AD) is an incurable, debilitating neurodegenerative disorder. Current biomarkers for AD diagnosis require expensive neuroimaging or invasive cerebrospinal fluid sampling, thus precluding early detection. Blood-based biomarker discovery in Alzheimer’s can faci...

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Bibliographic Details
Main Authors: Sherlyn Jemimah, Aamna AlShehhi, for the Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Medical Genomics
Subjects:
Alzheimer’s disease
Biomarkers
Neural network
Deep learning
Binary classification
Genomics
Online Access:https://doi.org/10.1186/s12920-023-01675-9

Internet

https://doi.org/10.1186/s12920-023-01675-9

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