TY  - BOOK
AU  - Pedersen,Mette
AU  - Hassan Nashaat,Neveen
AU  - Camesasca,Valentina
AU  - Hernández Villoria,Ramón
AU  - Das,Sneha
ED  - SpringerLink (Online service)
TI  - Voice-related Biomarkers
SN  - 9783032031341
AV  - RF1-547 
U1  - 617.51 23
PY  - 2026///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Otorhinolaryngology
KW  - Neurology 
KW  - Neurology
N1  - Preface -- . Methods -- 1. Committee on Biomarkers in Phoniatrics, Introduction -- 2. Overview of Voice Parameters in Parkinson’s Disease Allegedly as Biomarkers -- 3. AI-enhanced Voice Analysis for Neurologic Diseases -- 4. Modelling a Pre-clinical Screening Tool Based on Voice Biomarkers: The Case of Parkinson’s Disease -- 5. Glottal Inverse Filtering and Its Application in Automatic Classification of Diseases -- 6. (Bio)-markers and AI in Voice Disorders (Parkinson’s Disease): Opportunities and Challenges -- 7. Voice-related Biomarkers 2nd Union of European Phoniatricians/European Academy of Phoniatricians-British Laryngology Association, Joint Meeting -- 8. Software and Apps for Inverse Filtering of The Voice -- 9. Voice-related Biomarkers and Speech Measurements Determined with AI -- . Clinical Applications -- 10. Pathology of Voice-related Biomarkers in Laryngology -- 11. Voice-related Biomarkers in Neurodegenerative Disorders -- 12. Aspects of Genetics and Voice-related Biomarkers -- 13. Optical Coherence Tomography and Voice-related Biomarkers -- 14. Conclusion; Open Access
N2  - This Open Access book provides a comprehensive exploration of voice as a biomarker, addressing a current issue where engineers often analyze voice using sentences without describing or understanding voice as a set of defined parameters among others visually. This approach poses challenges for effectively treating voice disorders, as the features defined by engineers may not align with clinical needs. Stemming from the work of the Biomarker Committee group under the European Union of Phoniatricians (UEP), this book is the result of collaborative efforts and presents clinical studies aimed at bridging the gap between engineering analyses and clinical requirements. In recent years, many engineers have utilized software for voice analysis, often within continuous speech sequences, but without adequately defining voice features or specifying the choice of machine learning programs. Organized into 14 chapters, the volume begins with an overview of voice biomarkers and relevant literature, covering the fundamental physiology of voice biomarkers and examining voice pathology. The last chapters discuss genetics and molecular biology aspects. This book will serve as an invaluable resource for medical specialists in otolaryngology, phoniatrics, and neurology, offering insights and approaches to enhance the understanding and treatment of voice-related conditions
UR  - https://doi.org/10.1007/978-3-032-03134-1
ER  -