Identification of glomerulosclerosis using IBM Watson and shallow neural networks.

ABSTRACT:

Background

Advanced stages of different renal diseases feature glomerular sclerosis at a histological level which is observed by light microscopy on tissue samples obtained by performing a kidney biopsy. Computer-aided diagnosis (CAD) systems leverage the potential of artificial intelligence (AI) in healthcare to support physicians in the diagnostic process.

Methods

We propose a novel CAD system that processes histological images and discriminates between sclerotic and non-sclerotic glomeruli. To this goal, we designed, tested, and compared two artificial neural network (ANN) classifiers. The former implements a shallow ANN classifying hand-crafted features extracted from Regions of Interest (ROIs) by means of image-processing procedures. The latter, instead, employs the IBM

SUBMITTER: Pesce F 

PROVIDER: S-EPMC8765108 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature