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Cognitive Determinants of Dysarthria in Parkinson's Disease: An Automated Machine Learning Approach
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Outgoing claims: the papers this work cites, builds on, or argues with.
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inferredcites →https://doi.org/10.1016/j.parkreldis.2014.08.002openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.parkreldis.2016.05.018openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.parkreldis.2019.04.026openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.specom.2018.05.007openalex-snapshot
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inferredcites →https://doi.org/10.1016/s1474-4422(04)00854-3openalex-snapshot
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inferredcites →https://doi.org/10.1016/s1474-4422(12)70152-7openalex-snapshot
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Machine Learning for Parkinson’s Disease Detection: Analyzing Hybrid Voice Data With Spectral, Topological, and Random Matrix Methods
inferred← citeshttps://doi.org/10.1111/ene.15766openalex-snapshot
Patterns of hemispheric compromise in primary progressive apraxia of speech: From clinical profiling to differential diagnosis
inferred← citeshttps://doi.org/10.1155/2022/7223197openalex-snapshot
Severity Prediction over Parkinson’s Disease Prediction by Using the Deep Brooke Inception Net Classifier
inferred← citeshttps://doi.org/10.1159/000541581openalex-snapshot
Toolkit to Examine Lifelike Language v.2.0: Optimizing Speech Biomarkers of Neurodegeneration
inferred← citeshttps://doi.org/10.1177/1877718x261467587openalex-snapshot
Digital profiling of dysarthria in late- and early-onset Parkinson's disease
inferred← citeshttps://doi.org/10.1186/s40035-026-00558-0openalex-snapshot
From phenotype to biology: a multi-modal roadmap of biofluid, tissue, imaging, and digital biomarkers in Parkinson’s disease
inferred← citeshttps://doi.org/10.1212/wnl.0000000000200750openalex-snapshot
Automated Detection of Speech Timing Alterations in Autopsy-Confirmed Nonfluent/Agrammatic Variant Primary Progressive Aphasia
inferred← citeshttps://doi.org/10.1371/journal.pone.0303644openalex-snapshot
Machine learning for the detection and diagnosis of cognitive impairment in Parkinson’s Disease: A systematic review
inferred← citeshttps://doi.org/10.1371/journal.pone.0304272openalex-snapshot
Automated free speech analysis reveals distinct markers of Alzheimer’s and frontotemporal dementia
inferred← citeshttps://doi.org/10.14569/ijacsa.2023.0141258openalex-snapshot
Use of ANN, LSTM and CNN Classifiers for the New MSCC and BSCC Methods in the Detection of Parkinson's Disease by Voice Analysis
inferred← citeshttps://doi.org/10.1615/critrevbiomedeng.2022044813openalex-snapshot
Stack Ensemble Oriented Parkinson Disease Prediction Using Machine Learning Approaches Utilizing GridSearchCV-Based Hyper Parameter Tuning
inferred← citeshttps://doi.org/10.21203/rs.3.rs-7979633/v1openalex-snapshot
Voice onset time as a specific classifier for the PIGD subtype in Parkinson's Disease, independent of non-motor symptom severity
inferred← citeshttps://doi.org/10.2196/46105openalex-snapshot
Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review
inferred← citeshttps://doi.org/10.2196/59649openalex-snapshot
The Role of Machine Learning in Cognitive Impairment in Parkinson Disease: Systematic Review and Meta-Analysis
inferred← citeshttps://doi.org/10.2196/74200openalex-snapshot
Automated Speech Markers of Alzheimer Dementia: Test of Cross-Linguistic Generalizability
inferred← citeshttps://doi.org/10.2196/preprints.111048openalex-snapshot
A Multimodal Learning Approach Based on Self-narrative for Cognitive Impairment Prediction in Patients with Unipolar and Bipolar Disorder: Methodology Development and Application (Preprint)
inferred← citeshttps://doi.org/10.3389/fmed.2024.1453743openalex-snapshot
Utilizing deep learning models in an intelligent spiral drawing classification system for Parkinson’s disease classification
inferred← citeshttps://doi.org/10.3389/fnagi.2025.1704039openalex-snapshot
Machine learning methods for the detection and prediction of cognitive impairment in Parkinson’s disease: a systematic review and meta-analysis
inferred← citeshttps://doi.org/10.3389/fnhum.2022.1057578openalex-snapshot
Speech biomarkers of risk factors for vascular dementia in people with mild cognitive impairment
inferred← citeshttps://doi.org/10.3390/brainsci14020137openalex-snapshot
Unveiling the Diagnostic Potential of Linguistic Markers in Identifying Individuals with Parkinson’s Disease through Artificial Intelligence: A Systematic Review
inferred← citeshttps://doi.org/10.3390/diagnostics13132163openalex-snapshot
Deep Learning and Artificial Intelligence Applied to Model Speech and Language in Parkinson’s Disease
inferred← citeshttps://doi.org/10.3390/diagnostics15010073openalex-snapshot
Synchronous Analysis of Speech Production and Lips Movement to Detect Parkinson’s Disease Using Deep Learning Methods
inferred← citeshttps://doi.org/10.3390/diagnostics16050683openalex-snapshot
Longitudinal Evaluation of Dysarthria Progression in Patients with Parkinson’s Disease
inferred← citeshttps://doi.org/10.3390/electronics12040783openalex-snapshot
A Comprehensive Review on AI-Enabled Models for Parkinson’s Disease Diagnosis
inferred← citeshttps://doi.org/10.3758/s13428-023-02240-zopenalex-snapshot
Toolkit to Examine Lifelike Language (TELL): An app to capture speech and language markers of neurodegeneration
inferred← citeshttps://doi.org/10.3934/math.2024334openalex-snapshot
Modeling and diagnosis Parkinson disease by using hand drawing: deep learning model
inferred← citeshttps://doi.org/10.64898/2026.01.12.699086openalex-snapshot
Impact of Amazonian Dance on Speech Performance in People with Parkinson’s Disease
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