An ai-based system for tracking and monitoring kidney disease progression using medical imaging

Abstract

The present invention is related to an AI-based system for tracking and monitoring kidney disease progression using medical imaging. The system is configured to classify pathological conditions, including cysts, tumors, stones, and normal kidney tissue, while simultaneously tracking disease progression over time to support early clinical intervention and informed treatment planning. The system comprises a data acquisition module, a preprocessing module, a class-weighted deep learning classification module, a progression tracking module, and an integrated monitoring and reporting module. The system employs a class-weighted training methodology to address dataset imbalance and improve diagnostic accuracy for underrepresented disease categories. The progression tracking module analyzes sequential imaging data to detect subtle morphological changes, while the monitoring module consolidates outputs and generates automated clinical reports. By integrating these modules, the invention provides a reliable, scalable, and clinically actionable solution for continuous kidney disease monitoring, reducing misclassification, supporting proactive treatment planning, and advancing the state of the art in computer-assisted nephrology.