Published on in Vol 23, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26305, first published .
Detecting Parkinson Disease Using a Web-Based Speech Task: Observational Study

Detecting Parkinson Disease Using a Web-Based Speech Task: Observational Study

Detecting Parkinson Disease Using a Web-Based Speech Task: Observational Study

Journals

  1. Amprimo G, Masi G, Priano L, Azzaro C, Galli F, Pettiti G, Mauro A, Ferraris C. Assessment Tasks and Virtual Exergames for Remote Monitoring of Parkinson’s Disease: An Integrated Approach Based on Azure Kinect. Sensors 2022;22(21):8173 View
  2. Amato F, Saggio G, Cesarini V, Olmo G, Costantini G. Machine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey. Expert Systems with Applications 2023;219:119651 View
  3. Madruga M, Campos-Roca Y, Pérez C. Addressing smartphone mismatch in Parkinson’s disease detection aid systems based on speech. Biomedical Signal Processing and Control 2023;80:104281 View
  4. Ngo Q, Motin M, Pah N, Drotár P, Kempster P, Kumar D. Computerized analysis of speech and voice for Parkinson's disease: A systematic review. Computer Methods and Programs in Biomedicine 2022;226:107133 View
  5. Zhang T, Lin L, Xue Z. A voice feature extraction method based on fractional attribute topology for Parkinson’s disease detection. Expert Systems with Applications 2023;219:119650 View
  6. Zhang T, Lin L, Tian J, Xue Z, Guo X. Voice feature description of Parkinson’s disease based on co-occurrence direction attribute topology. Engineering Applications of Artificial Intelligence 2023;122:106097 View
  7. Gagliardi G. Natural language processing techniques for studying language in pathological ageing: A scoping review. International Journal of Language & Communication Disorders 2024;59(1):110 View
  8. Gupta R, Kumari S, Senapati A, Ambasta R, Kumar P. New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson’s disease. Ageing Research Reviews 2023;90:102013 View
  9. Idrisoglu A, Dallora A, Anderberg P, Berglund J. Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review. Journal of Medical Internet Research 2023;25:e46105 View
  10. Rahman W, Abdelkader A, Lee S, Yang P, Islam M, Adnan T, Hasan M, Wagner E, Park S, Dorsey E, Schwartz C, Jaffe K, Hoque E. A User-Centered Framework to Empower People with Parkinson's Disease. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2023;7(4):1 View
  11. Felix C, Johnston J, Owen K, Shirima E, Hinds S, Mandl K, Milinovich A, Alberts J. Explainable machine learning for predicting conversion to neurological disease: Results from 52,939 medical records. DIGITAL HEALTH 2024;10 View

Books/Policy Documents

  1. Rochester L, Del Din S, Hu M, Morgan C, Carroll C. Digital Technologies in Movement Disorders. View
  2. Adams J, Waddell E, Chunga N, Quinn L. Biomarkers for Huntington's Disease. View
  3. Jansi K, Vidhya S, Sandhia G. Intelligent Solutions for Cognitive Disorders. View