Machine Learning Shows Promise Predicting Progression of CKD to Kidney Failure

Pharmacy Times February 9, 2025
Gillian McGovern, Associate Editor

Key Takeaways

• Machine learning models effectively predict CKD progression using large clinical datasets, focusing on kidney function, complications, and etiologies.
• Age, sex, and serum albumin are significant variables in predicting CKD progression, with diabetes and hypertension as leading causes.
• Limitations include reliance on single time-point data and assumptions in variable categorization, necessitating further model refinement.
• The review underscores AI’s potential in CKD management, emphasizing the need for validation and refinement of predictive models.

These findings can lay the foundation for the development of machine learning models in chronic kidney disease (CKD) and kidney failure.

In health care, artificial intelligence (AI)—in particular, machine learning models—have demonstrated promise in the optimization of clinical decision-making and diagnosis. Chronic kidney disease (CKD)...

Today's Sponsors

Today's Sponsor