NCBI PubMed Central
open access
Comment on: "Prediction of Imminent Peritoneal Dialysis-Associated Peritonitis Using Time-Updated Electronic Health Records and Machine Learning: A Temporal Validation Study" [Letter].
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
- Development and Validation of Machine Learning Models for Predicting Initiation of Emergency Dialysis in Advanced Chronic Kidney Disease#394544
- Leveraging time-series electronic health records with large language models for chronic kidney disease diagnosis in primary care.#1080828
- Time-updated explainable machine learning predicts short-term mortality in peritoneal dialysis patients.#242230
- Time-updated explainable machine learning predicts short-term mortality in peritoneal dialysis patients.#240446
- Conceptualizing and evaluating the robustness of prediction models in healthcare#1166468
Record · ID 630817
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