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All issues Volume 56 (2023) ITM Web Conf., 56 (2023) 05002 References
Open Access
Issue
ITM Web Conf.
Volume 56, 2023
First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
Article Number 05002
Number of page(s) 6
Section Machine Learning & Neural Networks
DOI https://doi.org/10.1051/itmconf/20235605002
Published online 09 August 2023
  1. Surekha Tadse, Muskan Jain, Pankaj Chandankhede “Parkinson’s Detection Using Machine Learning” Published in: 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS) by IEEE. [Google Scholar]
  2. Sivachitra, M., Vijayachitra, S. “Parkinson’s disease prediction using machine learning approaches” Published in: 2013 Fifth International Conference on Advanced Computing (ICoAC). [Google Scholar]
  3. Haewon Byeon “Development of a depression in Parkinson’s disease prediction model using machine learning” in World J Psychiatry. 2020 Oct 19; 10(10): 234-244. Published online 2020 Oct 19. [CrossRef] [Google Scholar]
  4. Pawan Kumar Mall, Rajesh Kumar Yadav, Arun Kumar Rai, Vipul Narayan, Swapnita Srivastava, “Early Warning Signs Of Parkinson’s Disease Prediction Using Machine Learning Technique” by Journal of Pharmaceutical Negative Results in 2023 Special Issue, Vol. 14, p 2607-2615. 9p. [Google Scholar]
  5. Alexandre Boutet, Radhika Madhavan, Gavin J. B. Elias, Suresh E. Joel, Robert Gramer, Manish Ranjan, Vijayashankar Paramanandam, David Xu, Jurgen Germann, Aaron Loh, Suneil K. Kalia, Mojgan Hodaie, Bryan Li, Sreeram Prasad, Ailish Coblentz, Renato P. Munhoz, Jeffrey Ashe, Walter Kucharczyk, Alfonso Fasano & Andres M. Lozano. Article number: 3043 (2021) “Predicting optimal deep brain stimulation parameters for Parkinson’s disease using functional MRI and machine learning” Open Access article Published: 24 May 2021. [Google Scholar]
  6. Anant Dadu, Vipul Satone, Rachneet Kaur, Sayed Hadi Hashemi, Hampton Leonard, Hirotaka Iwaki, Mary B. Makarious, Kimberley J. Billingsley, Sara Bandres-Ciga, Lana J. Sargent, Alastair J. Noyce, Ali Daneshmand, Cornelis Blauwendraat, Ken Marek, Sonja W. Scholz, Andrew B. Singleton, Mike A. Nalls, Roy H. Campbell & Faraz Faghri Identification and prediction of Parkinson’s disease subtypes and progression using machine learning in two cohorts” Open Access article by Nature, Published: 16 December 2022 [Google Scholar]
  7. Md. Sakibur Rahman Sajal, Md. Tanvir Ehsan, Ravi Vaidyanathan, Shouyan Wang, Tipu Aziz & Khondaker Abdullah Al Mamun, “Telemonitoring Parkinson’s disease using machine learning by combining tremor andvoice analysis” Open Access article by ‘brain informatics. Springer open’ Published: 22 October 2020. [Google Scholar]
  8. Mehrbakhsh Nilashi, Rabab Ali Abumalloh, Behrouz Minaei-Bidgoli, Sarminah Samad, Muhammed Yousoof Ismail, Ashwaq Alhargan, Waleed Abdu Zogaan. “Predicting Parkinson’s Disease Progression: Evaluation of Ensemble Methods in Machine Learning” Volume 2022 | Article ID 2793361 from ‘hindawi.com’ Published 03 Feb 2022. [Google Scholar]
  9. Mary B. Makarious, Hampton L. Leonard, Dan Vitale, Hirotaka Iwaki, Lana Sargent, Anant Dadu, Ivo Violich, Elizabeth Hutchins, David Saffo, Sara Bandres-Ciga, Jonggeol Jeff Kim, Yeajin Song, Melina Maleknia, Matt Bookman, Willy Nojopranoto, Roy H. Campbell, Sayed Hadi Hashemi, Juan A. Botia, John F. Carter, David W. Craig, Kendall Van Keuren-Jensen, Huw R. Morris, John Hardy, Cornelis Blauwendraat, … Mike A. Nalls, “Multi-modality machine learning predicting Parkinson’s disease” in Nature.com Open Access article Published: 01 April 2022. [Google Scholar]
  10. M.S. Roobini, Yaragundla Rajesh Kumar Reddy, Udayagiri Sushmanth Girish Royal “Parkinson’s Disease Detection Using Machine Learning” Published in: 2022 International Conference on Communication, Computing and Internet of Things (IC3IoT). [Google Scholar]
  11. Ibrahim M. El-Hasnony, Sherif I. Barakat, and Reham R. Mostafa, “Optimized ANFIS Model Using Hybrid Metaheuristic Algorithms for Parkinson’s Disease Prediction in IoT Environment” in IEEE Access Received June 16, 2020, accepted June 25, 2020, date of publication June 29, 2020, date of current version July 8, 2020. [Google Scholar]
  12. Claas Ahlrichs and Michael Lawo “parkinson’s disease motor symptoms in machine learning: a review” Health Informatics- An International Journal (HIIJ) Vol. 2, No. 4, November 2013. [Google Scholar]
  13. Hakan Gunduz, “Deep Learning-Based Parkinson’s Disease Classification Using Vocal Feature Sets” Published in: IEEE Access (Volume: 7) [Google Scholar]
  14. Diba Ahmadi Rastegar, Nicholas Ho, Glenda M. Halliday & Nicolas Dzamko, «Parkinson’s progression prediction using machine learning and serum cytokines. Open Access article by Nature.com Published: 25 July 2019. [Google Scholar]
  15. Zaid Ajaz Moharkan, Harshul Garg, Tanupriya Chodhury, Praveen Kumar “A classification based Parkinson detection system” Published in: 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon). [Google Scholar]

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