Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Language Development01:22

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Baseline Differences in Cochlear Implant Candidates: Bilateral Traditional vs. Expanded Indications.

Journal of clinical medicine·2026
Same author

An Adult Autism Training With Case Studies and Standardized Patient Encounters for Internal Medicine and Family Medicine Residents.

MedEdPORTAL : the journal of teaching and learning resources·2026
Same author

Baseline Function Predicts Gains in Both Speech Recognition and Quality of Life After Cochlear Implantation.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology·2026
Same author

StyleGAN-based synthetic image augmentation for multi-class otoscopy image classification.

Scientific reports·2026
Same author

Role of Communication Partners in Pre-Cochlear Implant Decision-Making: A Scoping Review.

Ear and hearing·2026
Same author

Unique Natural History of Very Small Vestibular Schwannoma Substantiates Size Threshold Surveillance.

The Laryngoscope·2026

相关实验视频

Updated: Jun 29, 2026

Performing Intracochlear Electrocochleography During Cochlear Implantation
09:10

Performing Intracochlear Electrocochleography During Cochlear Implantation

Published on: March 8, 2022

4.9K

早期的耳植入物结果预测长期的语音识别.

Isabelle J Chau1,2,3, Ansley J Kunnath4,5,3, Andrew Gothard6

  • 1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA.

Ear and hearing
|December 17, 2025
PubMed
概括

早期耳植入物 (CI) 语音识别预测了长期的结果. 使用3个月得分的后勤回归模型准确估计了12个月的表现,帮助CI用户及时进行干预.

关键词:
耳植入物可以使用耳植入物.建模建模模型是什么预测结果 预测结果.语音识别 语音识别 语音识别

更多相关视频

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

733
Electrically Evoked Stapedius Reflex Measurements in Cochlear Implantation and Its Application in the Postoperative Fitting Process
07:00

Electrically Evoked Stapedius Reflex Measurements in Cochlear Implantation and Its Application in the Postoperative Fitting Process

Published on: June 21, 2024

1.4K

相关实验视频

Last Updated: Jun 29, 2026

Performing Intracochlear Electrocochleography During Cochlear Implantation
09:10

Performing Intracochlear Electrocochleography During Cochlear Implantation

Published on: March 8, 2022

4.9K
Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

733
Electrically Evoked Stapedius Reflex Measurements in Cochlear Implantation and Its Application in the Postoperative Fitting Process
07:00

Electrically Evoked Stapedius Reflex Measurements in Cochlear Implantation and Its Application in the Postoperative Fitting Process

Published on: June 21, 2024

1.4K

科学领域:

  • 听力学 听力学是指听力学.
  • 耳鼻喉科 耳鼻喉科 耳鼻喉科
  • 生物统计学 生物统计学

背景情况:

  • 早期识别耳植入物 (CI) 用户面临听力学结果不佳的风险,对于及时干预至关重要.
  • 优化长期CI益处需要在植入后的早期预测语音识别性能.

研究的目的:

  • 开发和评估逻辑回归模型,用于预测CI用户的12个月语音识别性能.
  • 评估早期语音识别分数和患者因子对长期CI结果的预测价值.

主要方法:

  • 一个回顾性队列研究,对625个后语言失聪的成年CI用户进行了回顾性队列研究.
  • 使用后勤回归来建模12个月后辅音-核心-辅音 (CNC) 词得分显著改善的可能性.
  • 模型结合了基线人口统计数据,聋的持续时间,CI前CNC得分,以及1个月或3个月的早期激活后CNC改善.

主要成果:

  • 82%的患者在植入后12个月内显示出CNC得分的改善.
  • 早期改善 (1或3个月) 是12个月结果的强有力的预测指标 (分别为45.72和22.22的OR).
  • 使用3个月数据的模型在验证队列中实现了最高的预测准确性 (AUC = 0.92).

结论:

  • 纳入早期CNC分数改进的模型显示出对12个月结果的强有力的预测歧视.
  • 使用3个月后CI语音识别数据的回归模型可以提供可靠的长期表现的早期估计.
  • 这种工具可以帮助临床医生识别那些可能受益于早期干预以优化CI结果的患者.