Automated Prediction of Kidney Failure in IgA Nephropathy with Deep Learning from Biopsy Images.

ABSTRACT:

Background and objectives

Digital pathology and artificial intelligence offer new opportunities for automatic histologic scoring. We applied a deep learning approach to IgA nephropathy biopsy images to develop an automatic histologic prognostic score, assessed against ground truth (kidney failure) among patients with IgA nephropathy who were treated over 39 years. We assessed noninferiority in comparison with the histologic component of currently validated predictive tools. We correlated additional histologic features with our deep learning predictive score to identify potential additional predictive features.

Design, setting, participants, & measurements

Training for deep learning was performed with randomly selected, digitalized, cortical Periodic acid-Schiff-stained secti

SUBMITTER: Testa F 

PROVIDER: S-EPMC9625090 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature