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Article

Machine learning-based genetic diagnosis models for hereditary hearing loss by the GJB2, SLC26A4 and MT-RNR1 variants.

EBioMedicine - 1 Jul 2021

Luo Xiaomei, Li Fengmei, Xu Wenchang, Hong Kaicheng, Yang Tao, Chen Jiansheng, Chen Xiaohe, Wu Hao

Abstract excerpt

BACKGROUND: Hereditary hearing loss (HHL) is the most common sensory deficit, which highly afflicts humans. With gene sequencing technology development, more variants will be identified and support genetic diagnoses, which is difficult for human experts to diagnose. This study aims to develop a machine learning-based genetic diagnosis model of HHL-related variants of GJB2, SLC26A4 and MT-RNR1. METHODS: This...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 34161886
DOI: 10.1016/j.ebiom.2021.103322
PMCID: PMC8237285

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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