Using AI to predict outcomes for people on continuous dialysis for acute kidney injury

Artificial Intelligence to Predict Outcomes in Patients with Acute Kidney Injury on Continuous Renal Replacement Therapy

NIH-funded research University of Alabama at Birmingham · NIH-11309119

This project uses artificial intelligence to predict survival and whether kidneys will recover for ICU patients receiving continuous dialysis for acute kidney injury.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of Alabama at Birmingham NIH-funded
Lab location1 site (Birmingham, United States)
Project IDNIH-11309119 on NIH RePORTER

What this research studies

If you are in the ICU with acute kidney injury and need continuous renal replacement therapy (continuous dialysis), researchers will use your routine health data to train deep learning models that predict survival and dialysis-free recovery. They will combine lab results, monitor data, treatments, and other clinical information to build and test these models. The team will also apply a Feasible Solution Algorithm to identify subgroups of patients who have different risks and might benefit from different care approaches. Models will be validated on separate patient datasets to check that predictions are accurate and reproducible.

Who could benefit from this research

Good fit: The ideal candidates are adult ICU patients with acute kidney injury who are receiving continuous renal replacement therapy (continuous dialysis).

Not a fit: People not in the ICU, those not receiving continuous dialysis, and patients on chronic maintenance dialysis are unlikely to directly benefit from this project.

Why it matters

Potential benefit: If successful, this could give doctors better, personalized information about likely survival and kidney recovery to guide dialysis decisions and post-ICU care.

How similar studies have performed: Some prior machine-learning work has predicted acute kidney injury outcomes, but accurate, widely accepted tools specifically for patients on continuous renal replacement therapy are limited, so this approach builds on prior AI work but remains relatively novel for this subgroup.

Where this research is happening

Birmingham, 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.