Machine learning for the diagnosis of Parkinson's disease: a review of literature
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and
assessment of clinical signs, including the characterization of a variety of motor symptoms …
assessment of clinical signs, including the characterization of a variety of motor symptoms …
The role of neural network for the detection of Parkinson's disease: a sco** review
Background: Parkinson's Disease (PD) is a chronic neurodegenerative disorder that has
been ranked second after Alzheimer's disease worldwide. Early diagnosis of PD is crucial to …
been ranked second after Alzheimer's disease worldwide. Early diagnosis of PD is crucial to …
A survey on siamese network: Methodologies, applications, and opportunities
Siamese network has obtained growing attention in real-life applications. In this survey, we
present an comprehensive review on Siamese network from the aspects of methodologies …
present an comprehensive review on Siamese network from the aspects of methodologies …
Multimodal triplet attention network for brain disease diagnosis
Multi-modal imaging data fusion has attracted much attention in medical data analysis
because it can provide complementary information for more accurate analysis. Integrating …
because it can provide complementary information for more accurate analysis. Integrating …
A computerized analysis with machine learning techniques for the diagnosis of Parkinson's disease: past studies and future perspectives
According to the World Health Organization (WHO), Parkinson's disease (PD) is a
neurodegenerative disease of the brain that causes motor symptoms including slower …
neurodegenerative disease of the brain that causes motor symptoms including slower …
A review of machine learning and deep learning algorithms for Parkinson's disease detection using handwriting and voice datasets
Parkinson's Disease (PD) is a prevalent neurodegenerative disorder with sig-nificant clinical
implications. Early and accurate diagnosis of PD is crucial for timely intervention and …
implications. Early and accurate diagnosis of PD is crucial for timely intervention and …
Innovative Speech-Based Deep Learning Approaches for Parkinson's Disease Classification: A Systematic Review
L van Gelderen, C Tejedor-García - arxiv preprint arxiv:2407.17844, 2024 - arxiv.org
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder
worldwide, frequently presents with early-stage speech impairments. Recent advancements …
worldwide, frequently presents with early-stage speech impairments. Recent advancements …
Personalized neural network for patient-specific health monitoring in IoT: a metalearning approach
The Internet of Things (IoT) has been widely applied in personal health monitoring on
biosignals. Conventional detection methods in the field count on a variety of heuristic criteria …
biosignals. Conventional detection methods in the field count on a variety of heuristic criteria …
Supervised speech representation learning for Parkinson's disease classification
Recently proposed automatic pathological speech classification techniques use
unsupervised auto-encoders to obtain a high-level abstract representation of speech. Since …
unsupervised auto-encoders to obtain a high-level abstract representation of speech. Since …
Temporal envelope and fine structure cues for dysarthric speech detection using CNNs
I Kodrasi - IEEE Signal Processing Letters, 2021 - ieeexplore.ieee.org
Deep learning-based techniques for automatic dysarthric speech detection have recently
attracted interest in the research community. State-of-the-art techniques typically learn …
attracted interest in the research community. State-of-the-art techniques typically learn …