Using machine learning to prevent kidney injury after heart surgery

Using Novel Machine Learning Methods to Personalize Strategies for Prevention of Persistent AKI after Cardiac Surgery

NIH-funded research Icahn School of Medicine at Mount Sinai · NIH-10894799

This study is looking to improve care for patients who might develop kidney problems after heart surgery by using smart computer techniques to create personalized plans that help manage their fluids and blood pressure better.

Quick facts

Grant typeCareer grant
Study typeNIH-funded research
Funding institutionIcahn School of Medicine at Mount Sinai NIH-funded
Lab location1 site (New York, United States)
Project IDNIH-10894799 on NIH RePORTER

What this research studies

This research aims to enhance the care of patients at risk for acute kidney injury (AKI) following cardiac surgery by utilizing advanced machine learning techniques. The project focuses on developing personalized prevention strategies that optimize patient management, including fluid status and blood pressure control. By analyzing data from patients undergoing cardiac procedures, the research seeks to identify effective interventions that can reduce the incidence of AKI. The principal investigator, trained in both nephrology and critical care, is committed to integrating health informatics and data science into clinical practice.

Who could benefit from this research

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

Not a fit: Patients who are not undergoing cardiac surgery or those with pre-existing severe kidney disease may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could significantly reduce the occurrence of acute kidney injury in patients undergoing cardiac surgery, leading to better overall health outcomes.

How similar studies have performed: Previous research has shown promise in using data-driven approaches to manage acute kidney injury, indicating that this method could lead to meaningful advancements in patient care.

Where this research is happening

New York, 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.
Last reviewed 2026-06-13 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.