Uncertainty-Gated SHAP-Dirichlet Refinement for MRI-Based Depression Classification
Structural MRI-based classification of major depressive disorder (MDD) remains challenging due to subtle, heterogeneous anatomical changes. We propose uncertainty-gated SHAP-Dirichlet refinement, a post-hoc reliability layer that improves predictions without retraining the classifier. The method retrieves similar labeled SHAP explanations, constructs Dirichlet class evidence, and selectively refines uncertain predictions through probabilistic fusion, while allowing unreliable cases to be deferred for expert review. We evaluate five classifiers on 504 SRPBS subjects (252 controls and 252 MDD patients) using 159 anatomical features and repeated nested cross-validation. Refinement improved a...
| Authors | Phuc Truong Loc Nguyen, Nguyen Truong Toan To, Truong Thanh Hung Nguyen et al. |
|---|---|
| Primary category | eess.IV |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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