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

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
  6. Rogers H, Hseu A, Kim J, Silberholz E, Jo S, Dorste A, Jenkins K. Voice as a Biomarker of Pediatric Health: A Scoping Review. Children 2024;11(6):684 View
  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

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