Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25247, first published .
Deep Learning Application for Vocal Fold Disease Prediction Through Voice Recognition: Preliminary Development Study

Deep Learning Application for Vocal Fold Disease Prediction Through Voice Recognition: Preliminary Development Study

Deep Learning Application for Vocal Fold Disease Prediction Through Voice Recognition: Preliminary Development Study

Journals

  1. Chen W, Tsao Y, Lai J, Hung C, Liu Y, Liu C. Real-Time Instance Segmentation of Metal Screw Defects Based on Deep Learning Approach. Measurement Science Review 2022;22(3):107 View
  2. Uloza V, Maskeliunas R, Pribuisis K, Vaitkus S, Kulikajevas A, Damasevicius R. An Artificial Intelligence-Based Algorithm for the Assessment of Substitution Voicing. Applied Sciences 2022;12(19):9748 View
  3. Compton E, Cruz T, Andreassen M, Beveridge S, Bosch D, Randall D, Livingstone D. Developing an Artificial Intelligence Tool to Predict Vocal Cord Pathology in Primary Care Settings. The Laryngoscope 2023;133(8):1952 View
  4. Yu X, Zhou S, Zou H, Wang Q, Liu C, Zang M, Liu T. Survey of deep learning techniques for disease prediction based on omics data. Human Gene 2023;35:201140 View
  5. Wandell G, Law A, Maxin A, Ha V, Wilson E, Nash M, Merati A, Whipple M, Meyer T. Defining the Performance of Clinician's Ability to Screen for Laryngeal Mass From Voice. Otolaryngology–Head and Neck Surgery 2023;168(6):1371 View
  6. Peterson Q, Fei T, Sy L, Froeschke L, Mendelsohn A, Berke G, Peterson D. Correlating Perceptual Voice Quality in Adductor Spasmodic Dysphonia With Computer Vision Assessment of Glottal Geometry Dynamics. Journal of Speech, Language, and Hearing Research 2022;65(10):3695 View
  7. Seok J, Kwon T. Artificial Intelligence for Clinical Research in Voice Disease. Journal of The Korean Society of Laryngology, Phoniatrics and Logopedics 2022;33(3):142 View
  8. Islam R, Abdel-Raheem E, Tarique M. A Novel Pathological Voice Identification Technique through Simulated Cochlear Implant Processing Systems. Applied Sciences 2022;12(5):2398 View
  9. Wang H, Zhang Z, Zhu Q, Wang X, Dong Z, Men G, Wang J, Lei J, Wang W. Batch skeleton extraction from ESPI fringe patterns using pix2pix conditional generative adversarial network. Optical Review 2022;29(2):97 View
  10. Kang H, Kang J, Lee S, Sim H. Applications and Performances of Artificial Intelligence in Assessment and Diagnosis of Communication Disorders: A Systematic Review of the Literatures. Communication Sciences & Disorders 2022;27(3):703 View
  11. Sakthivel S, Prabhu V, Jhaveri R. Optimal Deep Learning-Based Vocal Fold Disorder Detection and Classification Model on High-Speed Video Endoscopy. Journal of Healthcare Engineering 2022;2022:1 View
  12. Wang X, Wang T, Ding B. Voice Recognition and Evaluation of Vocal Music Based on Neural Network. Computational Intelligence and Neuroscience 2022;2022:1 View
  13. Calà F, Frassineti L, Manfredi C, Dejonckere P, Messina F, Barbieri S, Pignataro L, Cantarella G. Machine Learning Assessment of Spasmodic Dysphonia Based on Acoustical and Perceptual Parameters. Bioengineering 2023;10(4):426 View
  14. Suvvari T. The Role of Artificial Intelligence in Diagnosis and Management of Laryngeal Disorders. Ear, Nose & Throat Journal 2025;104(11):684 View
  15. Marchese M, Sensoli F, Campagnini S, Cianchetti M, Nacci A, Ursino F, D’Alatri L, Galli J, Carrozza M, Paludetti G, Mannini A. Artificial intelligence for the recognition of benign lesions of vocal folds from audio recordings. Acta Otorhinolaryngologica Italica 2023;43(5):317 View
  16. Liu G, Hodges J, Yu J, Sung C, Erickson‐DiRenzo E, Doyle P. End‐to‐end deep learning classification of vocal pathology using stacked vowels. Laryngoscope Investigative Otolaryngology 2023;8(5):1312 View
  17. Yu Y, Niu Q, Li X, Xue J, Liu W, Lin D. A Review of Fingerprint Sensors: Mechanism, Characteristics, and Applications. Micromachines 2023;14(6):1253 View
  18. Kim H, Park H, Park D, Im S, Lee S. Non-invasive way to diagnose dysphagia by training deep learning model with voice spectrograms. Biomedical Signal Processing and Control 2023;86:105259 View
  19. Watase T, Omiya Y, Tokuno S. Severity Classification Using Dynamic Time Warping–Based Voice Biomarkers for Patients With COVID-19: Feasibility Cross-Sectional Study. JMIR Biomedical Engineering 2023;8:e50924 View
  20. Tessler I, Primov-Fever A, Soffer S, Anteby R, Gecel N, Livneh N, Alon E, Zimlichman E, Klang E. Deep learning in voice analysis for diagnosing vocal cord pathologies: a systematic review. European Archives of Oto-Rhino-Laryngology 2024;281(2):863 View
  21. Lee J, Hamill C, Shnayder Y, Buczek E, Kakarala K, Bur A. Exploring the Role of Artificial Intelligence Chatbots in Preoperative Counseling for Head and Neck Cancer Surgery. The Laryngoscope 2024;134(6):2757 View
  22. Barlow J, Sragi Z, Rivera‐Rivera G, Al‐Awady A, Daşdöğen Ü, Courey M, Kirke D. The Use of Deep Learning Software in the Detection of Voice Disorders: A Systematic Review. Otolaryngology–Head and Neck Surgery 2024;170(6):1531 View
  23. Lee J, Seok J, Kim J, Kim H, Kwon T. Evaluating the Diagnostic Potential of Connected Speech for Benign Laryngeal Disease Using Deep Learning Analysis. Journal of Voice 2024 View
  24. Gupta R, Gunjawate D, Nguyen D, Jin C, Madill C. Voice disorder recognition using machine learning: a scoping review protocol. BMJ Open 2024;14(2):e076998 View
  25. Kim H, Song J, Park S, Lee Y. Classification of laryngeal diseases including laryngeal cancer, benign mucosal disease, and vocal cord paralysis by artificial intelligence using voice analysis. Scientific Reports 2024;14(1) View
  26. Nwosu O, Naunheim M. Artificial Intelligence in Laryngology, Broncho-Esophagology, and Sleep Surgery. Otolaryngologic Clinics of North America 2024;57(5):821 View
  27. Kim J, Seok J, Lee J, Lee J, Kwon T. Deep-Learning-Based Segmentation of Predefined Chunks in Connected Speech: A Retrospective Analysis. Journal of The Korean Society of Laryngology, Phoniatrics and Logopedics 2024;35(1):15 View
  28. Low D, Rao V, Randolph G, Song P, Ghosh S, Li-Jessen N. Identifying bias in models that detect vocal fold paralysis from audio recordings using explainable machine learning and clinician ratings. PLOS Digital Health 2024;3(5):e0000516 View
  29. Nobel S, Swapno S, Islam M, Safran M, Alfarhood S, Mridha M. A machine learning approach for vocal fold segmentation and disorder classification based on ensemble method. Scientific Reports 2024;14(1) View
  30. Torborg S, Kim A, Rameau A. New developments in the application of artificial intelligence to laryngology. Current Opinion in Otolaryngology & Head & Neck Surgery 2024;32(6):391 View
  31. Nguyen-Vo T, Do T, Nguyen B. Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds. Journal of Chemical Information and Modeling 2024;64(18):6957 View
  32. Er M, İlhan N. Voice Pathology Detection Based on Canonical Correlation Analysis Method Using Hilbert–Huang Transform and LSTM Features. Arabian Journal for Science and Engineering 2025;50(15):11693 View
  33. Song J, Kim H, Lee Y. Laryngeal disease classification using voice data: Octave-band vs. mel-frequency filters. Heliyon 2024;10(24):e40748 View
  34. Roitman A, Edelstain Y, Katzir C, Ofir H, Peleg N, Doweck I, Yanir Y. Harnessing machine learning in diagnosing complex hoarseness cases. American Journal of Otolaryngology 2025;46(1):104533 View
  35. Dritsas E, Trigka M, Troussas C, Mylonas P. Multimodal Interaction, Interfaces, and Communication: A Survey. Multimodal Technologies and Interaction 2025;9(1):6 View
  36. Xu W, Zhuang P, Yang H, Ge P, Huang D, Li G, Fu D, Chen Z. Chinese Expert Consensus for Assessment of Vocal Function (2024): Guidelines of the Subspecialty Group of Voice, Society of Otorhinolaryngology Head and Neck Surgery, Chinese Medical Association; Subspecialty Group of Laryngopharyngology, Editorial Board of Chinese Journal of Otorhinolaryngology Head and Neck Surgery. Journal of Voice 2025;39(2):469 View
  37. Kim Y, Dobko M, Li H, Shao T, Periyakoil P, Tipton C, Colasacco C, Serpedin A, Elemento O, Sabuncu M, Pitman M, Sulica L, Rameau A. A Deep‐Learning Model for Multi‐class Audio Classification of Vocal Fold Pathologies in Office Stroboscopy. The Laryngoscope 2025;135(7):2428 View
  38. Suleman A, Rutt A. Global utilization of artificial intelligence in the diagnosis and management of voice disorders over the past five years. Eye & ENT Research 2025;2(2):88 View
  39. Yao D, Koivu A, Simonyan K. Applications of Artificial Intelligence in Neurological Voice Disorders. World Journal of Otorhinolaryngology - Head and Neck Surgery 2025 View
  40. Pudasaini A, Al-Hawawreh M, Bouadjenek M, Hacid H, Aryal S. A comprehensive study of audio profiling: Methods, applications, challenges, and future directions. Neurocomputing 2025;640:130334 View
  41. Wei Y, Qin S, Liu F, Liu R, Zhou Y, Chen Y, Xiong X, Zheng W, Ji G, Meng Y, Wang F, Zhang R. Acoustic-based machine learning approaches for depression detection in Chinese university students. Frontiers in Public Health 2025;13 View
  42. Balo E, Ökte B, Selvi Balo S. Artificial intelligence in assessment and intervention of speech and language disorders: A literature review. The European Research Journal 2025;11(6):1235 View
  43. Ma S, Liao W, Zhang Y, Zhang F, Wang Y, Lu Z, Zhao C, Yu J, He P. Research on automatic assessment of the severity of unilateral vocal cord paralysis based on Mel-spectrogram and convolutional neural networks. BioMedical Engineering OnLine 2025;24(1) View
  44. Sahoo P, Mishra S, Brahma B, Bhoi A. An Optimized Multi-Level Convolutional Neural Network Model for Real Time Detection of Laryngeal Cancer. Journal of The Institution of Engineers (India): Series B 2025 View
  45. Kaur P, Chand T, Rani S. Integration of Artificial Intelligence in Laryngeal Cancer Diagnosis and Prognosis: A Comparative Analysis Bridging Traditional Medical Practices with Modern Computational Techniques. Archives of Computational Methods in Engineering 2025 View
  46. Zhang Y, Zou X, Yang J, Chen W, Liu J, Liang F, Li M. Multimodal laryngoscopic video analysis for assisted diagnosis of vocal fold paralysis. Computer Speech & Language 2026;96:101891 View
  47. Qian K, Zhao Z, Tan Y, Zhang W, Cho M, Zhu C, Tian F, Hu B, Yamamoto Y, Schuller B. Computer audition for healthcare: A survey on speech analysis. AI Open 2025;6:244 View

Books/Policy Documents

  1. Kim C, Lee S, Lee K. Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. View
  2. Farrokhian N, Bur A. Big Data in Otolaryngology. View
  3. Kavitha K, Rajkumar S, Gandhimathi (Usha) S. The Role of Artificial Intelligence in Advancing Applied Life Sciences. View
  4. Haddou N, Idrissi N, Chakib H. Advances on Intelligent Computing and Data Science II. View

Conference Proceedings

  1. Mousavi S, Ilanloo A. 2022 9th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS). Seven Staged Identity Recognition System Using Kinect V.2 Sensor View
  2. Lin W, Gao M, Ruan C, Zhong J. 2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI). Denoising for Intracranial Hemorrhage Images Using Autoencoder Based on CNN View
  3. Chen C, Hsu W, Lin T, Chen K, Tsou Y, Liu Y. 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). Classification of Vocal Cord Disorders: Comparison Across Voice Datasets, Speech Tasks, and Machine Learning Methods View
  4. Song J, Lee Y, Park S, Lee Y, Park H, Kim H. 2023 IEEE International Conference on Big Data (BigData). Enhancing Vocal-Based Laryngeal Cancer Screening with Additional Patient Information and Voice Signal Embedding View
  5. Merzougui N, Korba M, Amara F. 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS). Diagnosing Spasmodic Dysphonia with the Power of AI View
  6. Si G, Li M, Hou C, Sun Y, Li L. 2025 IEEE 8th Information Technology and Mechatronics Engineering Conference (ITOEC). Knowledge Graph Generation Algorithm Based on Bayesian Network View
  7. Mahajan A, Shukla M. 4TH INTERNATIONAL CONFERENCE ON FUNCTIONAL MATERIALS, MANUFACTURING, AND PERFORMANCES: ICFMMP-2023. Review on biometrics and fingerprint sensors materials View