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NCT07312929

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

Sponsor: University of Alberta

View on ClinicalTrials.gov

Summary

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.

Official title: SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS.

Key Details

Gender

All

Age Range

Any - Any

Study Type

OBSERVATIONAL

Enrollment

7500

Start Date

2026-06-01

Completion Date

2031-06-30

Last Updated

2026-01-12

Healthy Volunteers

No

Interventions

DEVICE

intermittent OR continuous renal replacement therapies

We will include any critically ill patient admitted to an intensive care unit requiring acute dialysis.