3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
Explainable AI Methods for Neuroimaging: Systematic Failures of Common Tools, the Need for Domain-Specific Validation, and a Proposal for Safe Application
Nys Tjade Siegel, James H. Cole, Mohamad Habes +3
Trustworthy interpretation of deep learning models is critical for neuroimaging applications, yet commonly used Explainable AI (XAI) methods lack rigorous validation, risking misin…
eess.IV2022★ 3 cited
Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies
Di Wang, Nicolas Honnorat, Peter T. Fox +4
Deep neural networks currently provide the most advanced and accurate machine learning models to distinguish between structural MRI scans of subjects with Alzheimer's disease and h…