关于人工智能检测语音病理学的全面审查:挑战和机遇
George S Liu1, Nedeljko Jovanovic2, C Kwang Sung1
1Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, California, USA.
概括
人工智能 (AI) 在检测和分类语音病理方面表现有前途. 关键的挑战包括各种数据集,有限的临床验证和不一致的报告,阻碍AI.
科学领域:
- 医疗信息学 医疗信息学
- 语言病理学 语音病理学
- 人工智能的人工智能
背景情况:
- 语音录音越来越多地使用人工智能 (AI) 进行分析,用于病态语音检测和分类.
- 人工智能在这个领域的应用在2000年至2023年期间,研究成果显著增加.
研究的目的:
- 调查关于人工智能应用用于声病理检测和分类的当前文献.
- 确定在语音病理学研究中推进AI的挑战和机会.
主要方法:
- 在PubMed,EMBASE,CINAHL和Scopus数据库中进行了系统的文献搜索.
- 包括使用人工智能检测或分类患者录音中的病态声音的研究,遵守PRISMA-ScR指南.
主要成果:
- 审查了82项研究,从2012年到2022年出版物的数量显著增加.
- 大多数研究侧重于检测 (88%) 和分类 (29%),很少有人评估特定的语音质量尺度 (5%).
- 显著的局限性包括缺乏AI模型验证报告 (17%) 和没有研究超出临床前开发或遵守AI报告准则.
结论:
- 人工智能对语音病理学检测和分类越来越感兴趣.
- 阻碍进步的主要挑战包括数据库异质性,缺乏临床验证研究和不一致的报告标准.
相关概念视频
01:31Respiratory System Abnormal Finding II: Palpation and Auscultation
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In assessing respiratory abnormalities, palpation and auscultation are critical tools for detecting and interpreting various pathophysiological changes. These techniques provide insight into underlying disorders by evaluating tactile sensations and sounds produced by the respiratory system.
Palpation Findings
During a respiratory assessment, palpation can reveal several vital abnormalities:
Palpation Findings
During a respiratory assessment, palpation can reveal several vital abnormalities:
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01:28Physical Assessment of the Respiratory Tract IV: Auscultation
383
Auscultation is a crucial component of the physical assessment of the respiratory tract. It offers valuable insights into airflow through the bronchial tree and potential lung obstructions. This process involves careful listening to breath, voice, and adventitious sounds, which can reveal a wealth of information about a patient's respiratory health.
Breath Sounds
Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
Breath Sounds
Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
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