Development and testing of an artificial intelligence tool for predicting end stage kidney disease in patients with immunoglobulin A nephropathy.

We have developed an artificial neural network prediction model for end-stage kidney disease (ESKD) in patients with primary immunoglobulin A nephropathy (IgAN) using a retrospective cohort of 948 patients with IgAN. Our tool is based on a two-step procedure of a classifier model that predicts ESRD, and a regression model that predicts development of ESKD over time. The classifier model showed a performance value of 0.82 (area under the receiver operating characteristic curve) in patients with a follow-up of five years, which improved to 0.89 at the ten-year follow-up.

Source: Kidney International - August 31, 2020 Category: Urology & Nephrology Authors: Francesco Paolo Schena, Vito Walter Anelli, Joseph Trotta, Tommaso Di Noia, Carlo Manno, Giovanni Tripepi, Graziella D ’Arrigo, Nicholas C. Chesnaye, Maria Luisa Russo, Maria Stangou, Aikaterini Papagianni, Carmine Zoccali, Vladimir Tesar, Rosanna Coppo Tags: clinical investigation Source Type: research