Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Learning Alerts for Acute Kidney Injury

Yale University · 2024
ClinicalTrials.gov · Datasets · License: Public Domain · 2024
Open Source ↗
acute-kidney-injuryna
The primary objective of this study is to determine whether the use of uplift (also known as Conditional Average Treatment Effect - CATE) modeling to empirically identify patients expected to benefit the most from AKI alerting and to target AKI alerts to these patients will reduce the rates of AKI progression, dialysis, and mortality.
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 806159
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