KidneyAI Dataset

Streamlining the Histopathologic Workflow in Diabetic Kidney Disease with Artificial Intelligence Summary A curated set of 3,928 PAS-stained mouse glomerulus images extracted from 30 whole slide images (WSIs) in a BTBR ob/ob diabetic nephropathy study. Each glomerulus is center-cropped and annotated independently by three expert kidney pathologists using a 5-class scheme: Normal, Mild, Moderate, Severe, and Excluded (uninformative). Contents Images: 3,928 cropped glomerulus patches (PAS stain), sourced from 30 WSIs. Labels: Triplicate expert scores per glomerulus (Experts 1–3) plus metadata for slide/study origin. Schema: Class labels {0,1,2,3,Excluded}; optional split files for cross-validation as used in the manuscript. File formats: Images: PNG Annotations and metadata: JSON Citation Please cite our paper “Streamlining the Histopathological Workflow in Diabetic Kidney Disease with Artificial Intelligence” when using this dataset.