NCBI PubMed Central
open access
Predicting first-year kidney graft loss at the time of donor offer using machine learning and competing-risk analysis in a Latin American cohort.
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
- A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study#450638
- Multidimensional System to Dynamically Predict Graft Survival After Kidney Transplantation#836193
- Machine learning-based evaluation of lipid biomarkers for cardiovascular risk prediction in chronic kidney disease: A cross-sectional study.#368327
- Short- and Long-Term Survival Prediction Using Different Prognostic Scores in Cardiovascular Surgeries.#12781
- UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120)#378014
Record · ID 154372
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