A two-stage pipeline using pretrained vision encoders with retrieval augmentation achieves 0.9423 held-out accuracy for leukemia versus normal detection, but ALL versus AML subtyping collapses under domain shift, showing within-domain performance comes largely from dataset artifacts.
Vista: vision transformer-attention enhanced cnn ensemble for optimized classification of acute lymphoblastic leukemia benign and progressive malignant stages,
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Retrieval-Augmented Vision Foundation Models for Robust Leukemia Cell Classification across Multiple Microscopy Datasets
A two-stage pipeline using pretrained vision encoders with retrieval augmentation achieves 0.9423 held-out accuracy for leukemia versus normal detection, but ALL versus AML subtyping collapses under domain shift, showing within-domain performance comes largely from dataset artifacts.