Robust, credible, and interpretable AI-based histopathological prostate cancer grading.

ABSTRACT:

Background

Prostate cancer (PCa) is among the most common cancers in men and its diagnosis requires the histopathological evaluation of biopsies by human experts. While several recent artificial intelligence-based (AI) approaches have reached human expert-level PCa grading, they often display significantly reduced performance on external datasets. This reduced performance can be caused by variations in sample preparation, for instance the staining protocol, section thickness, or scanner used. Another limiting factor of contemporary AI-based PCa grading is the prediction of ISUP grades, which leads to the perpetuation of human annotation errors.

Methods

We developed the prostate cancer aggressiveness index (PCAI), an AI-based PCa detection and grading framework that is traine

SUBMITTER: Westhaeusser F 

PROVIDER: S-EPMC11261944 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature