Machine learning methods for optimal prediction of motor outcome in Parkinson's disease.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date: Jan 7, 2020

Abstract

PURPOSE: It is vital to appropriately power clinical trials towards discovery of novel disease-modifying therapies for Parkinson's disease (PD). Thus, it is critical to improve prediction of outcome in PD patients.

Authors

  • Mohammad R Salmanpour
    Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran.
  • Mojtaba Shamsaei
    Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran.
  • Abdollah Saberi
    Department of Computer Engineering, Islamic Azad University, Tehran, Iran.
  • Ivan S Klyuzhin
    Department of Medicine, University of British Columbia, Vancouver, BC, Canada.
  • Jing Tang
    Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Vesna Sossi
    Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada.
  • Arman Rahmim

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