A Means of Assessing Deep Learning-Based Detection of ICOS Protein Expression in Colon Cancer.

ABSTRACT: Biomarkers identify patient response to therapy. The potential immune-checkpoint biomarker, Inducible T-cell COStimulator (ICOS), expressed on regulating T-cell activation and involved in adaptive immune responses, is of great interest. We have previously shown that open-source software for digital pathology image analysis can be used to detect and quantify ICOS using cell detection algorithms based on traditional image processing techniques. Currently, artificial intelligence (AI) based on deep learning methods is significantly impacting the domain of digital pathology, including the quantification of biomarkers. In this study, we propose a general AI-based workflow for applying deep learning to the problem of cell segmentation/detection in IHC slides as a basis for quantifying nuclear st

SUBMITTER: Sarker MMK 

PROVIDER: S-EPMC8345140 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature