现代临床神经心理学中的人工智能和自然语言处理:叙述性综述
1Department of Psychiatry and Biobehavioral Sciences, UCLA David Geffen School of Medicine, and Jane & Terry Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA.
The Clinical neuropsychologist
|August 18, 2025
概括
自然语言处理 (NLP) 将语音和文本转化为用于神经心理评估的数字生物标志物. NLP表现出高的诊断准确性,在各种疾病中提供客观,高效和公平的评估.
科学领域:
- 计算语言学 计算语言学
- 神经心理学 神经心理学
- 人工智能的人工智能
背景情况:
- 自然语言处理 (NLP) 提供了新的方法,用于从语音和文本生成客观的数字生物标志物.
- 传统的神经心理评估可以通过NLP的数据驱动洞察来增强.
研究的目的:
- 审查神经心理学的NLP研究,评估其对各种疾病的诊断效用,并建议临床采用.
- 评估NLP在提高神经心理评估中的客观性,效率和公平性方面的作用.
主要方法:
- 在主要数据库 (PubMed,Embase,PsycINFO,Scopus,Web of Science) 的范围搜索中,发现了56项实证研究.
- 研究对数据来源,语言特征,建模,验证和临床实用性进行了批判性评估.
主要成果:
- 在NLP中,可靠地提取词汇,语法和声学标记,具有高诊断准确性 (AUC>0.85).
- NLP方法通常优于传统测试,利用简短的语音或电子健康记录数据.
- 变压器模型促进实时支持,监控和反,但挑战包括数据限制和透明度.
结论:
- 神经心理学家需要计算语言素养和透明的报告才能有效地实施NLP.
- 解决算法偏见,代表性,隐私和可解释性对于NLP采用至关重要.
- 将NLP与神经成像和可穿戴设备相结合,以及联盟的发展,将促进客观和公平的神经心理学服务.
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