Inference-time aggregation of patient images, disorder centroids, and hybrid nearest-neighbor/centroid scores improves mean per-disorder top-1 retrieval accuracy on GMDB by up to 14.8 percentage points without retraining the GM-Arc encoder.
, author Hanani, Y
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Multi-Level Evidence Aggregation for Robust Facial Phenotype Retrieval in Rare Genetic Disorder Prioritization
Inference-time aggregation of patient images, disorder centroids, and hybrid nearest-neighbor/centroid scores improves mean per-disorder top-1 retrieval accuracy on GMDB by up to 14.8 percentage points without retraining the GM-Arc encoder.