A cross-sectional study of explainable machine learning in Alzheimer’s disease: diagnostic classification using MR radiomic features

A cross-sectional study of explainable machine learning in Alzheimer’s disease: diagnostic classification using MR radiomic features

IntroductionAlzheimer’s disease (AD) even nowadays remains a complex neurodegenerative disease and its diagnosis relies mainly on cognitive tests which have many limitations. On the other hand, qualitative imaging will not provide an early diagnosis because the radiologist will perceive brain atroph...

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Bibliographic Details
Main Authors: Stephanos Leandrou, Demetris Lamnisos, Haralabos Bougias, Nikolaos Stogiannos, Eleni Georgiadou, K. G. Achilleos, Constantinos S. Pattichis, Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-06-01
Series:Frontiers in Aging Neuroscience
Subjects:
Alzheimer’s disease
MRI
machine learning (ML)
radiomic
explainability and interpretability
Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2023.1149871/full

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https://www.frontiersin.org/articles/10.3389/fnagi.2023.1149871/full

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