ArticleSensors (Basel, Switzerland)2023
Artificial Intelligence-Based Voice Assessment of Patients with Parkinson's Disease Off and On Treatment: Machine vs. Deep-Learning Comparison.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning and wearable sensors for automated Parkinson's disease diagnosis aid: a systematic review.Journal of neurology · 2024Pooled it
- Rethinking the concept of disease modification in an evolving Parkinson's disease treatment landscape.Journal of Parkinson's disease · 2026Review
- A Pilot Study of VGGish-CNN as a Model for the Classification of Parkinson's Disease from a Control Group Using Speech Impairment, Integrated with Explainable Artificial Intelligence.Bioengineering (Basel, Switzerland) · 2026Article
- Non-Invasive Voice-Based Early Detection of Parkinson's Disease via Spectral Feature Analysis and Machine Learning Techniques.Bioengineering (Basel, Switzerland) · 2026Article
- Pilot Study Employing a Machine Learning Approach as a Potential Method for Predicting Parkinson's Disease Using Voice as a Digital Biomarker and the SHAP Approach for Feature Engineering.Bioengineering (Basel, Switzerland) · 2026Article
- Machine Learning-Based Detection of Parkinson's Disease From Arabic Speech: A Cross-Linguistic Validation Study.Journal of central nervous system disease · 2026Article
- Systematic review of unveiling the potential of AI using machine learning and deep learning methods in neurodegenerative diseases.PeerJ. Computer science · 2026Review
- Applications of Artificial Intelligence in Neurological Voice Disorders.World journal of otorhinolaryngology - head and neck surgery · 2025Review
- Through the Speech and Vocal Signals Hidden Secrets: An Explainable Methodology for Neurological Diseases Early Detection.Journal of healthcare informatics research · 2025Article
- Voice-Based Detection of Parkinson's Disease Using Machine and Deep Learning Approaches: A Systematic Review.Bioengineering (Basel, Switzerland) · 2025Review
- Multi-Modal Decentralized Hybrid Learning for Early Parkinson's Detection Using Voice Biomarkers and Contrastive Speech Embeddings.Sensors (Basel, Switzerland) · 2025Article
- Multi-Channel Spectro-Temporal Representations for Speech-Based Parkinson's Disease Detection.Journal of imaging · 2025Article
- Voice-Based Early Diagnosis of Parkinson's Disease Using Spectrogram Features and AI Models.Bioengineering (Basel, Switzerland) · 2025Article
- Micro- and nanoscale biosensing technologies for early diagnosis of Parkinson's disease.Mikrochimica acta · 2025Review
- AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.Brain sciences · 2025Review
- Automatic speech analysis combined with machine learning reliably predicts the motor state in people with Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Vocal performance evaluation of the intelligent note recognition method based on deep learning.Scientific reports · 2025Article
- Analysis of Voice, Speech, and Language Biomarkers of Parkinson's Disease Collected in a Mixed Reality Setting.Sensors (Basel, Switzerland) · 2025Article
- Exploring Spectrogram-Based Audio Classification for Parkinson's Disease: A Study on Speech Classification and Qualitative Reliability Verification.Sensors (Basel, Switzerland) · 2024Article
- Are smartphones and low-cost external microphones comparable for measuring time-domain acoustic parameters?European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's Disease (PD) is one of the most common non-curable neurodegenerative diseases. Diagnosis is achieved clinically on the basis of different symptoms with considerable delays from the onset of neurodegenerative processes in the central nervous system. In this study, we investigated early and full-blown PD patients based on the analysis of their voice characteristics with the aid of the most commonly employed machine learning (ML) techniques. A custom dataset was made with hi-fi quality recordings of vocal tasks gathered from Italian healthy control subjects and PD patients, divided into early diagnosed, off-medication patients on the one hand, and mid-advanced patients treated with L-Dopa on the other. Following the current state-of-the-art, several ML pipelines were compared usingdifferent feature selection and classification algorithms, and deep learning was also explored with a custom CNN architecture. Results show how feature-based ML and deep learning achieve comparable results in terms of classification, with KNN, SVM and naïve Bayes classifiers performing similarly, with a slight edge for KNN. Much more evident is the predominance of CFS as the best feature selector. The selected features act as relevant vocal biomarkers capable of differentiating healthy subjects, early untreated PD patients and mid-advanced L-Dopa treated patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.