MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set has been extensively used for the prediction of the progression of prodromal patients to Alzheimer's disease dementia. However, the deep learning community is not always aware of the biases that may contaminate neuroimaging data sets, which may lead to flawed results. In this case example, we demonstrated how ignoring the magnetic resonance (MR) field strength can bias performance of deep learning prediction when using MR images as input. Finally, we discussed options to overcome this problem.
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