DeepHistoClass: A Novel Strategy for Confident Classification of Immunohistochemistry Images Using Deep Learning.

ABSTRACT: A multitude of efforts worldwide aim to create a single-cell reference map of the human body, for fundamental understanding of human health, molecular medicine, and targeted treatment. Antibody-based proteomics using immunohistochemistry (IHC) has proven to be an excellent technology for integration with large-scale single-cell transcriptomics datasets. The golden standard for evaluation of IHC staining patterns is manual annotation, which is expensive and may lead to subjective errors. Artificial intelligence holds much promise for efficient and accurate pattern recognition, but confidence in prediction needs to be addressed. Here, the aim was to present a reliable and comprehensive framework for automated annotation of IHC images. We developed a multilabel classification of 7848 complex

SUBMITTER: Ghoshal B 

PROVIDER: S-EPMC8476775 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature