Machine Learning and Artificial Intelligence Algorithms to Optimize the Performance and Delivery of Acute Dialysis

Starting soon

Conditions studied: Renal Dialysis, Renal Replacement Therapy, Renal Diseases, Quality Health Care

In brief

SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS. Hypothesis: Can the investigators develop and implement Machine Learning and Artificial Intelligence Algorithms into Clinical Information Systems to Optimize the Prescription, Delivery, and Performance of Acute Dialysis? Objective(s): 1. Identify variables surrounding identified Key Performance Indicators that may be used by Machine Learning and Artificial Intelligence algorithms to optimize the prescription and performance of acute dialysis. 2. Develop Machine Learning and Artificial Intelligence algorithms to help guide the prescription and delivery of acute dialysis in the development of Clinical Decision Support tools and Best Practice Advisories and create a ML/AI Augmented SMART DIALYSIS Digital Dashboard. 3. Implement and evaluate the performance of the developed Machine Learning and Artificial Intelligence algorithms on patient-centered and health economic outcomes. 4. Validate and benchmark the performance of the evaluated Machine Learning and Artificial Intelligence algorithms across multiple jurisdictions.

Key facts

Study ID

NCT07312929

Run by

University of Alberta

People needed

7500

Starts

2026-06-01

Expected to finish

2031-06-30

Last updated by the study team

2026-01-12

Who can join

Age: any. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Patients admitted to an intensive care unit (ICU) who require acute renal replacement therapy, either intermittent or continuous.

You may not qualify if…

• Receipt of renal replacement therapy for less than 24 hours.
• Pre-existing end-stage kidney disease.

Full record on ClinicalTrials.gov

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