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Article

A Multiple-Instance Learning-Based Convolutional Neural Network Model to Detect the IDH1 Mutation in the Histopathology Images of Glioma Tissues.

Journal of computational biology : a journal of computational molecular cell biology - 1 Aug 2020

Cui Danni, Liu Yingying, Liu Gang, Liu Lei

Abstract excerpt

The IDH1 mutation is the most frequent somatic mutation in gliomas, and it has an important impact on the treatment outcome of gliomas. Clinically, the gold standard methods for the IDH mutation detection are the immunohistochemistry and gene sequencing techniques, whereas using the histopathology images of the glioma tissues for IDH mutation identification has not been reported. In this study, we propose a...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 31905004
DOI: 10.1089/cmb.2019.0410

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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