Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Cognitive Phenotyping of Parkinson's Disease Patients Via Digital Analysis of Spoken Word Properties.

Movement disorders : official journal of the Movement Disorder Society - 1 Nov 2025

Ferrante Franco J, Escobar Grisales Daniel, López María Fernanda, Lopes da Cunha Pamela, Sterpin Lucas Federico, Vonk Jet M J, Chaná Cuevas Pedro, Estienne Claudio, Hesse Eugenia, Amoruso Lucía, Orozco Arroyave Juan Rafael, García Adolfo M

Abstract excerpt

BACKGROUND: Cognitive symptoms are highly prevalent in Parkinson's disease (PD), often manifesting as mild cognitive impairment (MCI). Yet, their detection and characterization remain suboptimal because standard approaches rely on subjective impressions derived from lengthy, univariate tests. OBJECTIVE: We examined whether digital analysis of verbal fluency predicts cognitive status in PD. METHODS: We asked 464...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Aged
Share to Cognitive Dysfunction

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Neuropsychological Tests

Share to Parkinson Disease

Share to Phenotype

Share to Semantics

Source

Open in PubMed Open full text

Identifiers

PMID: 40798929
DOI: 10.1002/mds.70005
PMCID: PMC13093902

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Cognitive Phenotyping of Parkinson's Disease Patients Via Digital Analysis of Spoken Word Properties.PMID 40798929Read ↗

Digital Phenotyping of Parkinson’s Disease via Natural Language ProcessingSemantic proximity Read ↗

Automated Online Speech Analytics Reveal Language and Affective Changes in Parkinson’s DiseaseSemantic proximity Read ↗

Cognitive structure and progression in Parkinson’s Disease: Insights from a tablet-based assessmentSemantic proximity Read ↗

Lexical Markers of Disordered Speech in Primary Progressive Aphasia and ‘Parkinson-plus’ DisordersSemantic proximity Read ↗

Evaluation of a speech-based AI system for early detection of Alzheimer’s disease remotely via smartphonesSemantic proximity Read ↗

Digital language markers distinguish frontal from right anterior temporal lobe atrophy in frontotemporal dementiaSemantic proximity Read ↗

Lexical and acoustic speech features relating to Alzheimer’s disease pathologySemantic proximity Read ↗

A Comparative Analysis of Parkinson’s Disease Diagnosis Approaches Using Drawing-Based Datasets: Utilizing Large Language Models, Machine Learning, and Fuzzy OntologiesSemantic proximity Read ↗

Generative Large Language Models in the Clinical Management of Alzheimer’s Disease and Mild Cognitive ImpairmentSemantic proximity Read ↗

Verbal fluency tests assess global cognitive status but have limited diagnostic differentiation: Evidence from a large-scale examination of six neurodegenerative diseasesSemantic proximity Read ↗

Clinically meaningful metrics of speech in neurodegenerative disease: Quantification of speech intelligibility and naturalness in ataxiaSemantic proximity Read ↗

Smartphone-Derived Ocular Motor Biomarkers Enable AI to Assess Neurodegeneration in Huntington’s DiseaseSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.