Language Impairment in Alzheimer's Disease-Robust and Explainable Evidence for AD-Related Deterioration of Spontaneous Speech Through Multilingual Machine Learning.
Language Impairment in Alzheimer's Disease-Robust and Explainable Evidence for AD-Related Deterioration of Spontaneous Speech Through Multilingual Machine Learning.
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DOI：
10.3389/fnagi.2021.642033
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发表时间：
2021
影响因子：
4.8
通讯作者：
König A
中科院分区：
文献类型：
--
作者：
Lindsay H;Tröger J;König A
阿尔茨海默病（AD）是一种广泛的神经退行性疾病，影响全球数百万人，并且最显著地与广泛的认知下降（包括语言障碍）相关。图片描述任务通常用于监测AD患者的语言障碍。由于深入分析由此产生的自发语音需要大量的手动资源，高级自然语言处理（NLP）与机器学习（ML）相结合代表了一个有前途的机会。然而，在这个应用研究领域，NLP和ML方法并不一定能确保对AD认知语言障碍的强大临床可操作见解，必须采取额外的预防措施以确保结果的临床有效性和普遍性。在这项研究中，我们通过多语言特征统计的计算方法检测AD中的语言障碍增加了概括性。我们包括154名参与者（78名健康受试者，76名AD患者），来自两种不同的语言（106名讲英语和47名讲法语）。每个参与者完成一个图片描述任务，除了电池的神经心理测试。每一个回答都被记录下来并手工转录。由此，使用NLP资源提取特定于任务的、语义的、句法的和非语言的特征。使用推理统计，我们确定的语言功能，不包括任务的具体功能，这是显着的两种语言，因此代表“概括”的迹象，认知语言障碍的AD。在第二步中，我们使用各种分类器在二元歧视ML场景（AD与健康）中评估了英语，法语和两种语言的所有特征以及可推广的特征。在英语、法语和多语种情况下，可推广的语言功能集优于所有语言功能集。语义特征是最具概括性的，而非语言特征在语言之间没有重叠。多语种模式显示，英文和法文的错误分布相等。通过利用多语言统计与理论驱动的方法相结合，我们确定了AD相关的语言障碍，概括了一个单一的语料库或语言模型语言障碍作为临床相关的认知症状。我们发现一个主要的障碍，除了轻微的句法障碍，可能混淆了额外的认知功能受损的语义。
Alzheimer’s disease (AD) is a pervasive neurodegenerative disease that affects millions worldwide and is most prominently associated with broad cognitive decline, including language impairment. Picture description tasks are routinely used to monitor language impairment in AD. Due to the high amount of manual resources needed for an in-depth analysis of thereby-produced spontaneous speech, advanced natural language processing (NLP) combined with machine learning (ML) represents a promising opportunity. In this applied research field though, NLP and ML methodology do not necessarily ensure robust clinically actionable insights into cognitive language impairment in AD and additional precautions must be taken to ensure clinical-validity and generalizability of results. In this study, we add generalizability through multilingual feature statistics to computational approaches for the detection of language impairment in AD. We include 154 participants (78 healthy subjects, 76 patients with AD) from two different languages (106 English speaking and 47 French speaking). Each participant completed a picture description task, in addition to a battery of neuropsychological tests. Each response was recorded and manually transcribed. From this, task-specific, semantic, syntactic and paralinguistic features are extracted using NLP resources. Using inferential statistics, we determined language features, excluding task specific features, that are significant in both languages and therefore represent “generalizable” signs for cognitive language impairment in AD. In a second step, we evaluated all features as well as the generalizable ones for English, French and both languages in a binary discrimination ML scenario (AD vs. healthy) using a variety of classifiers. The generalizable language feature set outperforms the all language feature set in English, French and the multilingual scenarios. Semantic features are the most generalizable while paralinguistic features show no overlap between languages. The multilingual model shows an equal distribution of error in both English and French. By leveraging multilingual statistics combined with a theory-driven approach, we identify AD-related language impairment that generalizes beyond a single corpus or language to model language impairment as a clinically-relevant cognitive symptom. We find a primary impairment in semantics in addition to mild syntactic impairment, possibly confounded by additional impaired cognitive functions.
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DOI：
10.1080/01690960802299378
发表时间：
2009-05-01
期刊：
Language and cognitive processes
影响因子：
--
作者：
Baese-Berk M;Goldrick M
通讯作者：
Goldrick M
DOI：
10.1093/brain/awt269
发表时间：
2013-12
期刊：
Brain : a journal of neurology
影响因子：
--
作者：
Ahmed S;Haigh AM;de Jager CA;Garrard P
通讯作者：
Garrard P
影响因子：
4.3
作者：
Fraser, Kathleen C.;Fors, Kristina Lundholm;Kokkinakis, Dimitrios
通讯作者：
Kokkinakis, Dimitrios
影响因子：
4.3
作者：
Calza, Laura;Gagliardi, Gloria;Tamburini, Fabio
通讯作者：
Tamburini, Fabio
DOI：
10.3233/jad-200888
发表时间：
2020
期刊：
Journal of Alzheimer's disease : JAD
影响因子：
--
作者：
de la Fuente Garcia S;Ritchie CW;Luz S
通讯作者：
Luz S