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利用文本挖掘揭示30年痴呆症言语生物标志物研究

Unveiling 30 years of research on speech biomarker of dementia using text mining.

作者信息

Oh Chorong, Park Min Sook

机构信息

Department of Communication Sciences and Disorders, College of Health Sciences, University of Kentucky, Lexington, KY, USA.

School of Information, College of Communication and Information, Florida State University, Tallahassee, FL, USA.

出版信息

Digit Health. 2025 Jul 29;11:20552076251360901. doi: 10.1177/20552076251360901. eCollection 2025 Jan-Dec.

Abstract

INTRODUCTION

As the incidence and prevalence of dementia continue to rise, there is a critical need for more cost- and time-efficient diagnostic tools. Analysis of speech prosody has emerged as a promising noninvasive biomarker, potentially offering a more accessible approach to dementia identification. However, the absence of a longitudinal analysis of thematic evolution within the extensive literature in this domain has resulted in a notable knowledge gap.

METHODS

We conducted a text mining analysis of publications from the past 30 years to identify key research trends, thematic patterns, and associated topics.

RESULTS

Our analysis yielded three major findings: a marked acceleration in research activity since 2020, a convergence of clinical needs with technological advancements, and the inherently interdisciplinary nature of this field.

DISCUSSION

These findings not only underscore the dynamic evolution of dementia research but also highlight the potential of speech prosody analysis as a viable, noninvasive diagnostic tool. Future research integrating multidisciplinary approaches and evaluating diagnostic values of speech prosody is warranted.

摘要

引言

随着痴呆症的发病率和患病率持续上升,迫切需要更具成本效益和时间效率的诊断工具。语音韵律分析已成为一种有前景的非侵入性生物标志物,可能为痴呆症识别提供一种更易获得的方法。然而,在该领域的大量文献中,缺乏对主题演变的纵向分析,导致了明显的知识空白。

方法

我们对过去30年的出版物进行了文本挖掘分析,以确定关键研究趋势、主题模式和相关主题。

结果

我们的分析得出了三个主要发现:自2020年以来研究活动显著加速、临床需求与技术进步的融合以及该领域固有的跨学科性质。

讨论

这些发现不仅强调了痴呆症研究的动态演变,还突出了语音韵律分析作为一种可行的非侵入性诊断工具的潜力。未来有必要开展整合多学科方法并评估语音韵律诊断价值的研究。

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