This paper is in the following e-collection/theme issue:

Digital Health Reviews (1558) Artificial Intelligence (1779) Machine Learning (1770) Decision Support for Health Professionals (1361) Digital Biomarkers and Digital Phenotyping (231)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46105, first published .
Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review

Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review

Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review

Authors of this article:

Alper Idrisoglu1 Author Orcid Image ;   Ana Luiza Dallora1 Author Orcid Image ;   Peter Anderberg1, 2 Author Orcid Image ;   Johan Sanmartin Berglund1 Author Orcid Image
Article Authors Cited by (29) Tweetations (12) Metrics

Journals

  1. Eguchi K, Yaguchi H, Kudo I, Kimura I, Nabekura T, Kumagai R, Fujita K, Nakashiro Y, Iida Y, Hamada S, Honma S, Takei A, Moriwaka F, Yabe I. Differentiation of speech in Parkinson’s disease and spinocerebellar degeneration using deep neural networks. Journal of Neurology 2024;271(2):1004 View
  2. Pham T, Holmes S, Zou L, Patel M, Coulthard P. Diagnosis of pathological speech with streamlined features for long short-term memory learning. Computers in Biology and Medicine 2024;170:107976 View
  3. Calvache-Mora C, Soláque L, Velasco A, Peñuela L. Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method. Revista de Investigación e Innovación en Ciencias de la Salud 2024;6(1):24 View
  4. Ur Rehman M, Shafique A, Azhar Q, Jamal S, Gheraibia Y, Usman A. Voice disorder detection using machine learning algorithms: An application in speech and language pathology. Engineering Applications of Artificial Intelligence 2024;133:108047 View
  5. Bensoussan Y, Elemento O, Rameau A. Voice as an AI Biomarker of Health—Introducing Audiomics. JAMA Otolaryngology–Head & Neck Surgery 2024;150(4):283 View
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  7. Granov R, Vedad S, Wang S, Durham A, Shah D, Pasinetti G. The Role of the Neural Exposome as a Novel Strategy to Identify and Mitigate Health Inequities in Alzheimer’s Disease and Related Dementias. Molecular Neurobiology 2025;62(1):1205 View
  8. Cai J, Song Y, Wu J, Chen X. Voice Disorder Classification Using Wav2vec 2.0 Feature Extraction. Journal of Voice 2024 View
  9. Vivekanandam B. AI-Enabled Medical Assessment and Assistance for Vocal Disorders: A Comparative Study. Journal of Artificial Intelligence and Capsule Networks 2024;6(3):340 View
  10. Wujian Y, Yingcong Z, Yuehai C, Yijun L, Zhiwei M. Post-Stroke Dysarthria Voice Recognition based on Fusion Feature MSA and 1D. Computer Methods in Biomechanics and Biomedical Engineering 2024:1 View
  11. Lim W, Chiu S, Peng P, Jang J, Lee S, Lin C, Kim H. A cross-language speech model for detection of Parkinson’s disease. Journal of Neural Transmission 2025;132(4):579 View
  12. Naranjo L, Pérez C, Merino D. A data ensemble-based approach for detecting vocal disorders using replicated acoustic biomarkers from electroglottography. Sensing and Bio-Sensing Research 2025;47:100741 View
  13. Ge C, Cretu E. Using Polymeric Piezoelectric Accelerometers to Measure Vocal Pitches and Tones. IEEE Transactions on Instrumentation and Measurement 2025;74:1 View
  14. Bélisle-Pipon J, Anibal J, Bahr R, Bedrick S, Coleman O, Dorr D, Evans B, Fagherazzi G, Gelbard A, Ghosh S, Ho A, Jackson C, Joachim D, Kourtis L, Krussel A, Lahav A, Leuze B, MacDonald B, Miller G, Mohan V, Naunheim M, Powell M, Rameau A, Ramphal S, Ravitsky V, Reavis C, Salvi Cruz S, Toghranegar J, Vogel A, Watts S, Yracheta J, Zhao R, Bensoussan Y. Interactive Panel Summaries of the 2024 Voice AI Symposium. Frontiers in Digital Health 2025;7 View
  15. Brockmann‐Bauser M. How Well Will AI Help Recognize Voice Disorders? A State‐of‐the‐art Review of Current Acoustic Assessment Strategies and Future Applications. World Journal of Otorhinolaryngology - Head and Neck Surgery 2025 View
  16. Moothedan E, Boyer M, Watts S, Abdel-Aty Y, Ghosh S, Rameau A, Sigaras A, Elemento O, Bensoussan Y. The Bridge2AI-voice application: initial feasibility study of voice data acquisition through mobile health. Frontiers in Digital Health 2025;7 View
  17. Gallano G, Giglio A, Ferre A. Artificial Intelligence in Speech-Language Pathology and Dysphagia: A Review From Latin American Perspective and Pilot Test of LLMs for Rehabilitation Planning. Journal of Voice 2025 View
  18. Školoudík D. The potential of artificial intelligence in the diagnosis and treatment of neurological diseases. Neurologie pro praxi 2025;26(2):154 View

Books/Policy Documents

  1. Dixit A, Tyagi A, Sharma S, Dhir S. Generative AI Techniques for Sustainability in Healthcare Security. View
  2. Smilarubavathy G, Keerthana S, Nidhya R, Priscilla T, Pavithra D. Smart Factories for Industry 5.0 Transformation. View

Conference Proceedings

  1. Pham T. 2024 IEEE First International Conference on Artificial Intelligence for Medicine, Health and Care (AIMHC). Textures and Networks of Healthy and Pathological voice Signals View
  2. Al-Dhief F, Abdul Latiff N, Malik N, Baki M, Muhammad N, Abbood Albadr M. 2024 IEEE 7th International Symposium on Telecommunication Technologies (ISTT). Investigating Fast Learning Network for Voice Pathology Detection View
  3. Regondi S, Pugliese R, Mahroo A. 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE). Towards a Predictive Model of Speech Signatures: Insights from Spectral Analysis and Generative AI Models View
  4. Chagas A, S. Lobo P, Felix J, do Nascimento H, Salvini R. Anais da XII Escola Regional de Informática de Goiás (ERI-GO 2024). Analyzing the Impact of Voice Data Replication on Machine Learning Models for Parkinson’s Disease Diagnosis View
  5. Perelli G, Panzino A, Casula R, Micheletto M, Orrù G, Marcialis G. 2024 IEEE International Workshop on Information Forensics and Security (WIFS). Vulnerabilities in Machine Learning-Based Voice Disorder Detection Systems View
  6. Kumar V, Gupta S. 2024 IEEE Silchar Subsection Conference (SILCON 2024). Preliminary Analysis of Physiological Signals in Relation to Early Indication of Paralysis Disorder Using Neural Network Approach View
  7. Boujraine K, Laaidi N, Ezzine A, Satori H. 2024 3rd International Conference on Embedded Systems and Artificial Intelligence (ESAI). A Comprehensive Review of intelligent Voice Disorder Diagnosis: Techniques, Databases, and Machine Learning Approaches View
  8. Pal N, Shrivas A, Roy R, Shetty S, Gidaye G, Deshpande S. 2025 3rd International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC). Predicting Vocal Pathologies: A Multi-Dataset Machine Learning Framework for Healthcare Applications View
  9. Yousef A, Hunter E. The 1st International Online Conference on Bioengineering. Machine Learning Classifiers for Voice Health Assessment Under Simulated Room Acoustics View