CKD Path

CKD Path is a centralized platform for visualizing, modeling, and integrating multimodal CKD data, with clinician-facing dashboards tailored to nephrologists and primary care providers. Built on a FastAPI backend and React/TypeScript frontend, it integrates with the AI Data Hub and processes structured OMOP clinical data to support real-time patient monitoring, CKD trajectory modeling, and clinical decision-making.

The application enables researchers and clinicians to:

• Visualize & filter dedicated patient pages with longitudinal vitals, clinical visit history, and dynamic dataset filtering for clinical trend identification.
• Predict and visualize eGFR trajectory with CKD stage annotations, AI-driven prediction modeling, and an Intervention Simulator for exploring clinical scenarios.
• Support clinical decision through KDIGO guideline integration, a medication table, kidney risk references, and risk-stratification visual enhancements.
• Score kidney failure risk with validated risk calculations (KFRE/Tangri) mapped to clinical risk bands.
• Visit CKD Path

CKD Path establishes a reusable, transparent framework for CKD care modeling by leveraging standardized OMOP data structures and open-source technologies. It is built for interpretability, keeping predictions to stay clinically explainable, with transparent fallback behavior when data is incomplete.