Enhancing Podocyte Degenerative Changes Identification With Pathologist Collaboration: Implications for Improved Diagnosis in Kidney Diseases.

ABSTRACT: Podocyte degenerative changes are common in various kidney diseases, and their accurate identification is crucial for pathologists to diagnose and treat such conditions. However, this can be a difficult task, and previous attempts to automate the identification of podocytes have not been entirely successful. To address this issue, this study proposes a novel approach that combines pathologists' expertise with an automated classifier to enhance the identification of podocytopathies. The study involved building a new dataset of renal glomeruli images, some with and others without podocyte degenerative changes, and developing a convolutional neural network (CNN) based classifier. The results showed that our automated classifier achieved an impressive 90.9% f-score. When the pathologists used

SUBMITTER: Barros GO 

PROVIDER: S-EPMC11515860 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature