Deep learning automation of MEST-C classification in IgA nephropathy.

Date publication

février 2023

Journal

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association

Auteurs

Membres identifiés du Cancéropôle Est :
Pr DUCLOUX Didier , Pr MARTIN Laurent

Tous les auteurs :
Jaugey A, Maréchal E, Tarris G, Paindavoine M, Martin L, Chabannes M, de la Vega MF, Chaintreuil M, Robier C, Ducloux D, Crépin T, Felix S, Jacq A, Calmo D, Tinel C, Zanetta G, Rebibou JM, Legendre M

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/36792061

Résumé

Though the MEST-C classification is among the best prognostic tools in IgA nephropathy, it has a wide inter-observer variability between specialized pathologists and others. Therefore, we trained and evaluated a tool using Neural Network to automate the MEST-C grading.

Mots clés

IgA nephropathy, MEST-C classification, convolutional neural network, deep learning, kidney biopsy

Référence

Nephrol Dial Transplant. 2023 02 15;: