Higher performance for women than men in MRI-based Alzheimer’s disease detection

Introduction Although machine learning classifiers have been frequently used to detect Alzheimer’s disease (AD) based on structural brain MRI data, potential bias with respect to sex and age has not yet been addressed. Here, we examine a state-of-the-art AD classifier for potential sex and age bias...

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Bibliographic Details
Published in:	Alzheimer's research & therapy Vol. 15; no. 1; pp. 84 - 13
Main Authors:	Klingenberg, Malte, Stark, Didem, Eitel, Fabian, Budding, Céline, Habes, Mohamad, Ritter, Kerstin
Format:	Journal Article
Language:	English
Published:	London BioMed Central 20.04.2023 Springer Nature B.V BMC
Subjects:	Age Algorithms Alzheimer Disease - diagnostic imaging Alzheimer's disease Artificial intelligence Bias Biomedical and Life Sciences Biomedicine Brain research Classification Cognitive Dysfunction - diagnosis Data integrity Datasets Decision making Deep learning Female Gender differences Geriatric Psychiatry Geriatrics/Gerontology Humans Machine Learning Magnetic resonance imaging Magnetic Resonance Imaging - methods Male MRI Neural networks Neuroimaging Neurology Neurosciences Registration Sex Women Deep learning Alzheimer’s disease MRI Bias Sex
ISSN:	1758-9193, 1758-9193
Online Access:	Get full text
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