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 …
Addressing challenges in speaker anonymization to maintain utility while ensuring privacy of pathological speech
S Tayebi Arasteh, T Arias-Vergara… - Communications …, 2024 - nature.com
Background Integration of speech into healthcare has intensified privacy concerns due to its
potential as a non-invasive biomarker containing individual biometric information. In …
potential as a non-invasive biomarker containing individual biometric information. In …
The effect of speech pathology on automatic speaker verification: a large-scale study
Navigating the challenges of data-driven speech processing, one of the primary hurdles is
accessing reliable pathological speech data. While public datasets appear to offer solutions …
accessing reliable pathological speech data. While public datasets appear to offer solutions …
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy
Developing robust and effective artificial intelligence (AI) models in medicine requires
access to large amounts of patient data. The use of AI models solely trained on large multi …
access to large amounts of patient data. The use of AI models solely trained on large multi …
Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning
S Tayebi Arasteh, C Kuhl, MJ Saehn, P Isfort… - Scientific Reports, 2023 - nature.com
Developing robust artificial intelligence (AI) models that generalize well to unseen datasets
is challenging and usually requires large and variable datasets, preferably from multiple …
is challenging and usually requires large and variable datasets, preferably from multiple …
Exploring federated learning for speech-based parkinson's disease detection
A Sarlas, A Kalafatelis, G Alexandridis… - Proceedings of the 18th …, 2023 - dl.acm.org
Parkinson's Disease is the second most prevalent neurodegenerative disorder, currently
affecting as high as 3% of the global population. Research suggests that up to 80% of …
affecting as high as 3% of the global population. Research suggests that up to 80% of …
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models
Developing robust artificial intelligence (AI) models that generalize well to unseen datasets
is challenging and usually requires large and variable datasets, preferably from multiple …
is challenging and usually requires large and variable datasets, preferably from multiple …
[HTML][HTML] Analyzing Wav2Vec 1.0 Embeddings for Cross-Database Parkinson's Disease Detection and Speech Features Extraction
O Klempíř, R Krupička - Sensors, 2024 - mdpi.com
Advancements in deep learning speech representations have facilitated the effective use of
extensive unlabeled speech datasets for Parkinson's disease (PD) modeling with minimal …
extensive unlabeled speech datasets for Parkinson's disease (PD) modeling with minimal …
Parkinson's Disease Detection Based on Vocal Biomarkers and Machine Learning Approach
Parkinson's disease (PD) must be identified early to provide prompt treatment and better
patient outcomes. This study looks into using machine learning methods in conjunction with …
patient outcomes. This study looks into using machine learning methods in conjunction with …
The Impact of Speech Anonymization on Pathology and Its Limits
Integration of speech into healthcare has intensified privacy concerns due to its potential as
a non-invasive biomarker containing individual biometric information. In response, speaker …
a non-invasive biomarker containing individual biometric information. In response, speaker …