Editorial: Digital Linguistic Biomarkers: Beyond Paper and Pencil Tests [PDF]
Frontiers in Psychology, 2021 Over the last few years, a growing body of linguistic studies have been devoted to the clinical domain, and neuroscience and mental health are no exception to this. However, many of the factors underlying cognitive and neuropsychiatric symptoms are hard to foresee; furthermore, it is often difficult to predict the disease trajectory.
Gloria Gagliardi +4 more
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Editorial: Digital linguistic biomarkers: beyond paper and pencil tests, volume II [PDF]
Frontiers in Psychology, 2023 As the co-editors of the second edition of “Digital linguistic biomarkers: beyond paper and pencil tests,” we are pleased to present this Research Topic of cutting-edge research articles that continue to explore the exciting intersection of linguistics, technology, and cognitive science.
Jon Andoni Duñabeitia +4 more
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CharMark: character-level Markov modeling for interpretable linguistic biomarkers of cognitive decline [PDF]
Frontiers in Digital HealthDementia, one of the most prevalent neurodegenerative diseases, affects millions worldwide. Understanding linguistic markers of dementia is crucial for elucidating how cognitive decline manifests in speech patterns.
Kevin Mekulu, Faisal Aqlan, Hui Yang
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Character-level linguistic biomarkers for precision assessment of cognitive decline: a symbolic recurrence approach [PDF]
Frontiers in Aging NeuroscienceEarly-stage Alzheimer's disease (AD) remains difficult to assess using conventional linguistic or cognitive assessments, which often overlook subtle and individualized disruptions in speech.
Kevin Mekulu, Faisal Aqlan, Hui Yang
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Editorial: Linguistic biomarkers of neurological, cognitive, and psychiatric disorders: verification, analytical validation, clinical validation, and machine learning [PDF]
Frontiers in PsychologyRatree Wayland +3 more
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Screening for early Alzheimer’s disease: enhancing diagnosis with linguistic features and biomarkers
Frontiers in Aging NeuroscienceIntroductionResearch has shown that speech analysis demonstrates sensitivity in detecting early Alzheimer’s disease (AD), but the relation between linguistic features and cognitive tests or biomarkers remains unclear.
Chia-Ju Chou +14 more
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Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline. [PDF]
Annu Int Conf IEEE Eng Med Biol Soc, 2023 IEEE EMBC ...
Wang Z +8 more
europepmc +4 more sources
Detecting CSF-validated Alzheimer’s disease from spontaneous speech in German: an interpretable end-to-end machine-learning framework [PDF]
Frontiers in NeurologyBackgroundSpeech and language impairments, long recognized as early symptoms of Alzheimer’s disease (AD), can now be quantified with unprecedented precision due to recent advances in natural language processing (NLP) and artificial intelligence (AI ...
Daniel Wiechmann +8 more
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Speech analysis for differentiating bipolar disorder and major depressive disorder during euthymic states [PDF]
Annals of General PsychiatryObjective Differentiating major depressive disorder (MDD) from bipolar disorder (BP) is crucial for early diagnosis and targeted treatment. This study investigates speech, linguistic biomarkers, and machine learning models to differentiate between the ...
Jhen-Wu Lai +3 more
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Validating Digital Linguistic Features as Potential Biomarkers of Alzheimer's Disease [PDF]
Alzheimers DementAbstract Background Speech features derived from verbal responses to cognitive tests have been shown to indicate mild cognitive impairment and later risk of Alzheimer's Disease (AD). However, research in validating speech features using established AD biomarkers remains limited. This study aims
Huang H +7 more
europepmc +3 more sources