Conceptio › Archive › arXiv (All)
arXiv (All) open access

Interpretable Multiple-Instance Learning of Glomerular Pathomics and Subtype Ratios for eGFR Classification

Shi, Tianyu et al.
arXiv (All) · Papers
Open Source ↗Direct PDF ↓
computer-vision-and-pattern-recognitionimage-and-video-processing
Chronic kidney disease is characterized by structural alterations in renal tissue and progressive loss of kidney function. While glomerular subtype ratios provide a compact and clinically meaningful summary of glomerular composition, representing pathomic information using whole-slide image (WSI)-le
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1535704
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive