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

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.