Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

Journal: Brain stimulation
PMID: 26140956

Abstract

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization.

Authors

  • Reuben R Shamir
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
  • Trygve Dolber
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
  • Angela M Noecker
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
  • Benjamin L Walter
    Department of Neurology, Case Western Reserve University, Cleveland, OH, USA; Neurological Institute, University Hospitals Case Medical Center, Cleveland, OH, USA.
  • Cameron C McIntyre
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Neurology, Case Western Reserve University, Cleveland, OH, USA. Electronic address: ccm4@case.edu.

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