Data leakage in feature selection invalidates reported classification accuracy for autism diagnosis from fMRI

We read with interest the article by Vidya et al.1 reporting 98.2% accuracy for autism spectrum disorder (ASD) classification using deep learning on functional MRI data from the ABIDE I dataset. While the authors' focus on interpretability is commendable, we identified a critical methodological flaw that invalidates the reported performance metrics.