摘要
突发性聋是一种常见的耳科疾病,全球发病率较高。听力损失会极大程度降低患者生活质量,并带来沉重的公共医疗负担。为改善患者的预后,现有研究报告了一些影响预后的关键因素。最近,也有研究开始利用机器学习建立突聋预后的预测模型。充分了解影响预后的因素,建立预测预后的模型,有利于提高预测预后准确性,指导治疗方案的调整,到达改善预后的目的,最终使患者受益。
Sudden sensorineural hearing loss(SSNHL)is a common otologic disease.It affects numerous people around the world annually.Hearing loss significantly affects patients’daily life and causes great burden on public health.Researchers have reported critical factors to improve its prognosis.Recently,some researches have been reported to construct prognostic models of SSNHL by artificial learning.Discovering prognostic factors and constructing predictive models are beneficial to improve the condition’s prognosis and ultimately benefit patients.
作者
杨安妮
李琦
李湘平
YANG Anni;LI Qi;LI Xiangping(Department of Otolaryngology-Head and Neck Surgery,Nanfang Hospital,Southern Medical University,1838 North Guangzhou Avenue,Guangzhou 510515,Guangdong,P.R.China)
出处
《中华耳科学杂志》
CSCD
北大核心
2021年第2期306-310,共5页
Chinese Journal of Otology
基金
南方医科大学南方医院院长基金(NO.2019B011)。
关键词
突发性聋
预后因素
机器学习
预后模型
Sudden sensorineural hearing loss
Prognostic factors
Machine learning
Predictive prognosis models
