Applied research in CKD self-management technology.

Kidney Tech Alliance is exploring how explainable and context-aware artificial intelligence can support people managing chronic kidney disease.

Our research examines the use of AI to interpret validated information, explain patterns, support comparison of dietary choices, and provide longitudinal coaching.

The goal is not to replace nephrologists, renal dietitians, or other healthcare professionals. The research focuses on how technology can help individuals better understand their own tracked information and engage more effectively in kidney health self-management.

Traditional nutrition tracking tools typically report nutrient totals. Kidney Tech Alliance is researching whether comparative methods can provide additional insight by evaluating how different dietary choices affect an individual's current phosphorus and potassium tracking position.

This research considers multiple nutrient constraints, current tracked intake, nutrient-data quality, and differences among available choices.

The objective is to determine whether comparative choice information can improve the usefulness and understandability of digital CKD self-management tools.

Dietary tracking and clinical information are often maintained in separate systems. Kidney Tech Alliance is researching whether selected clinical information can provide meaningful context for digital CKD self-management tools.

Research areas may include longitudinal laboratory information, CKD-related health context, and patient-generated dietary data.

The Alliance is also exploring standards-based health data interoperability, including FHIR-enabled approaches, to understand how authorized clinical information may responsibly support future kidney health technologies.