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BRCA2 Protein

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New Approach for Risk Estimation Algorithms of Negativeness Detection with Modelling Supervised Machine Learning Techniques.

Disease markers
gene testing is a difficult, expensive, and time-consuming test which requires excessive work load. The identification of the gene mutations is significantly important in the selection of treatment and the risk of secondary cancer. We aimed to deve...

DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.

Genome medicine
BACKGROUND: Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and ris...

Deep Learning for Detecting BRCA Mutations in High-Grade Ovarian Cancer Based on an Innovative Tumor Segmentation Method From Whole Slide Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
BRCA1 and BRCA2 genes play a crucial role in repairing DNA double-strand breaks through homologous recombination. Their mutations represent a significant proportion of homologous recombination deficiency and are a reliable effective predictor of sens...