Keywords: Alzheimer's Disease, Machine Learning/Artificial IntelligenceRecent studies have shown Clever Hans effects in e.g. a widely used MRI tumor dataset. Clever Hans was a horse in the early 20th century that could supposedly do some arithmetic, although it only reacted to unintended cues of its owner. Inspired by these insights, we used T1w images from the ADNI database and removed the texture using threshold binarization. By using a standard deep neural network we separated images from Alzheimer's patients (n=404) from normal controls (n=905). This study revealed that volumetric measures are overwhelmingly relevant for the classification, while textures (T1w-contrast variations) are neglectable.
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