摘要
人工耳蜗植入是当前帮助重度和极重度听障患者恢复部分听力的最有效方法,术后康复效果存在较大的个体差异。为了更好地探讨术后康复效果的影响因素,机器学习逐渐被应用于预测人工耳蜗植入患者的术后康复效果。但相关研究仍处于起步阶段,还存在诸如样本量不足、数据特征缺乏多样化等问题。建议未来研究扩大样本量,并优化机器学习的模型,充分挖掘影响预测人工耳蜗植入后康复效果的因素,使机器学习更好地应用于人工耳蜗植入领域。
Cochlear implantation is the most effective method to restore hearing in patients with severe and profound hearing impairment.There are individual differences in rehabilitation after cochlear implantation.In order to better understand the underlying factors of rehabilitation,machine learning has been gradually applied to the rehabilitation prediction of cochlear implant patients.Since related literature is still in its infancy,many problems still remain unresolved,such as insufficient sample size and lack of diversification of data features.We suggest that future research may expand the sample size,optimize machine learning models,and fully explore the predictive factors affecting the rehabilitation of cochlear implantation,and make machine learning a better tool in the area of cochlear implantation.
作者
赖恺瀛
刘佳浩
左笑怡
梁茂金
王穗苹
LAI Kaiying;LIU Jiahao;ZUO Xiaoyi;LIANG Maojin;WANG Suiping(Guangzhou Institute of Educational Research,Guangzhou 510180,China;School of Psychology,South China Normal University,Guangzhou 510631,China;Department of Otolaryngology,Sun Yat-sen Memorial Hospital,Sun Yat-Sen University,Guangzhou 510120,China;Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents(South China Normal University)Ministry of Education China,Guangzhou 510631,China)
出处
《听力学及言语疾病杂志》
北大核心
2025年第2期182-187,共6页
Journal of Audiology and Speech Pathology
基金
国家自然科学基金面上项目(32171051)
广东省自然科学基金-面上项目(2022)(2022A1515010311)
广州市校(院)联合资助(登峰医院)基础研究项目(202201020478)。
关键词
机器学习
人工耳蜗植入
康复效果
预测
模型
Machine learning
Cochlear implantation
Rehabilitation effect
Prediction
Model
