Fig. 5 | Scientific Reports

Fig. 5

From: Multiple instance learning using pathology foundation models effectively predicts kidney disease diagnosis and clinical classification

Fig. 5

Attention heatmaps of models using Virchow2 and ResNet50 in the disease classification analysis. A sample slide was obtained from a patient diagnosed with AIN in the UT cohort. Attention scores for each diagnostic label (HC, AIN, and DKD) were used to visualize the regions of focus for the models in the disease classification task. Heatmaps were generated using the Turbo colormap. Attention heatmaps of the Virchow2-based model (a) and the ResNet50-based model (b) for each label (HC, AIN, and DKD) are shown. The original H&E-stained images were used as references. H&E hematoxylin–eosin, HC healthy control, AIN acute interstitial nephritis, DKD diabetic kidney disease. Scale bar = 100 μm.

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