Using machine learning to detect and treat acute kidney injury early

Using Machine Learning for Early Recognition and Personalized Treatment of Acute Kidney Injury

['FUNDING_R01'] · UNIVERSITY OF CHICAGO · NIH-10894908

This study is looking to help doctors spot kidney problems early in hospitalized patients by using smart computer tools to analyze health records, so they can provide personalized treatment and improve recovery.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF CHICAGO (nih funded)
Locations1 site (CHICAGO, UNITED STATES)
Trial IDNIH-10894908 on ClinicalTrials.gov

What this research studies

This research focuses on improving the early detection and personalized treatment of acute kidney injury (AKI) in hospitalized patients. By utilizing machine learning algorithms and natural language processing, the study aims to analyze both structured and unstructured data from electronic health records to identify patients at high risk for severe AKI before it becomes clinically apparent. This proactive approach seeks to enhance patient outcomes by allowing for earlier interventions, potentially reducing the risk of complications associated with AKI.

Who could benefit from this research

Good fit: Ideal candidates for this research are hospitalized patients who are at risk for developing acute kidney injury.

Not a fit: Patients who are not hospitalized or those who do not have risk factors for acute kidney injury may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to earlier diagnosis and more effective treatment of acute kidney injury, ultimately improving patient outcomes and reducing healthcare costs.

How similar studies have performed: Previous research has shown promise in using machine learning for early detection of various medical conditions, indicating potential success for this novel approach in AKI.

Where this research is happening

CHICAGO, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.