Deep learning su dati clinici longitudinali e immunologici per la stratificazione della sindrome nefrosica

Abstract

This study explores lymphocyte profiles as non-invasive biomarkers for classification of pediatric nephrotic syndrome (NS). Using retrospective clinical and immunological data from 205 patients, the aim is to develop a predictive model based on Long Short-Term Memory to identify NS subtypes. By comparing models with and without immunological data, the study will assess the value of immune profiles. The goal is to support personalized management while reducing the need for invasive procedures.