Artificial intelligence-assisted diagnosis of glomerular nephritis using a pathological image analysis approach: a multicentre model development and validation study.

ABSTRACT:

Background

The diagnosis of glomerular nephritis (GN) is based on kidney biopsy analysis by nephropathologists, a process that is manual, subjective, and labor-intensive, inevitably leading to interobserver variability. This study aims to develop and validate an artificial intelligence (AI)-assisted model for diagnosing GN using digital histological images from kidney biopsy.

Methods

This multicentre model development and validation study included patients who underwent a kidney biopsy and were diagnosed with focal segmental glomerulosclerosis (FSGS), IgA nephropathy (IgAN), membranous nephropathy (MN), or minimal change disease (MCD). The study cohorts were derived from three institutions: Nanfang Hospital of Southern Medical University, Jinyu Diagnostic Center, and Huayin

SUBMITTER: Nie S 

PROVIDER: S-EPMC12538914 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature