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

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.

Objective

Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication.

Methods

Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions

SUBMITTER: Shamir RR 

PROVIDER: S-EPMC5015434 | biostudies-literature | 2015 Nov-Dec

REPOSITORIES: biostudies-literature