Project Mission

The project focuses on the definition and implementation of a decision support system aimed at facilitating the early diagnosis and monitoring of pediatric patients with posterior urethral valves (PUV). This condition is often difficult to diagnose accurately without resorting to invasive examinations. Moreover, it increases the risk of chronic kidney disease, a condition associated with high morbidity and mortality.

The proposed system will integrate clinical, anthropometric, anamnestic, and instrumental data through a multimodal analysis, allowing for an accurate and timely prediction—prior to surgical intervention—of which patients may be affected by PUV and which patients may be at an increased risk of developing chronic kidney disease during subsequent follow-up.

The combined analysis of different data sources will not only enhance the accuracy and reliability of the proposed tool but, thanks to the use of Explainable Artificial Intelligence (XAI) techniques, will also provide medical specialists with a clear understanding of the diagnostic decision-making processes. This will be crucial in supporting healthcare professionals in the patient care process.