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Article

Identifying genetic risk variants associated with noise-induced hearing loss based on a novel strategy for evaluating individual susceptibility.

Hearing research - 1 Aug 2021

Jiang Zhuang, Fa Botao, Zhang Xunmiao, Wang Jiping, Feng Yanmei, Shi Haibo, Zhang Yue, Sun Daoyuan, Wang Hui, Yin Shankai

Abstract excerpt

BACKGROUND: The overall genetic profile for noise-induced hearing loss (NIHL) remains elusive. Herein we proposed a novel machine learning (ML) based strategy to evaluate individual susceptibility to NIHL and identify the underlying genetic risk variants based on a subsample of participants with extreme phenotypes. METHODS: Five features (age, sex, cumulative noise exposure [CNE], smoking, and alcohol drinking...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 34157653
DOI: 10.1016/j.heares.2021.108281

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