arXiv (All)
open access
Seeing Abnormal from Normal: Glomerular Abnormality in Representations of Normal Renal Morphology
Fine-grained evaluation of glomerular pathology must distinguish normal glomeruli from abnormalities such as global and segmental glomerulosclerosis, obsolescent, ischemic, solidified, disappearing, and atubular glomeruli. Supervised classification requires labeled examples of every category, which
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
- Artificial Intelligence-based Techniques to Characterize KIdney Microstructure on Histological ImagEs#836277
- Clinical application of deep learning-based measurement of glomerular morphometry in IgAN.#469186
- Deep Learning-Assisted Classification of Urinary Red Blood Cell Morphology for Glomerular Hematuria Screening: A Pilot Study.#1091487
- Multiparametric MRI in Healthy Volunteers and CKD Patients#855993
- Patient and Tumor Characteristics can Predict Nondiagnostic Renal Mass Biopsy Findings#383776
Record · ID 1014038
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
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
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive