NCBI PubMed Central
open access
CD3+ T-cell count prediction for anti-thymocyte globulin treatment monitorization in kidney transplant recipients: a machine learning model.
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
- Thymoglobulin Induction in Kidney Transplant Recipients#1172316
- Effect of Thymoglobulin Versus Basiliximab on Regulatory T Cell Function in Live Donor Kidney Transplant Recipients#1174214
- Machine learning model for predicting hypotension following continuous renal replacement therapy initiation in end-stage kidney disease patients: a SHAP-interpretable approach.#242325
- Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study.#265307
- Efficacy and Safety of Two Anti-T-lymphocyte Immune Globulin (ATG-F) Induction Regimens in Anew Kidney Transplant Patients#868996
Record · ID 338430
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