Title Information
Title
Decoding Biomarkers of Parkinson’s Disease Using Convolutional Regression Networks
Abstract
The applications of convolutional neural networks (CNN) are nearly endless. As a popular method for image classification, they have demonstrated the ability to categorize Parkinson’s symptomology using neurophysiologic spectral data as inputs. Regression networks, whose outputs are continuous versus categorical or binary, can potentially be a precise tool for identifying neural biomarkers of disease. Insights into such features may advance the implementation of closed-loop deep brain stimulation (DBS).
Name
Name Part
Lee, Shane
Role
Role Term (marcrelator) (authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/aut")
Author
Name
Name Part
Liu, David
Role
Role Term (marcrelator) (authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/aut")
Author
Name
Name Part
Zheng, Bryan
Role
Role Term (marcrelator) (authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/aut")
Author
Name
Name Part
Asaad, Wael
Role
Role Term (marcrelator) (authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/aut")
Author
Name: Corporate
Name Part
Brown University. Alpert Medical School. Scholarly Concentration Program. Non-Scholarly Concentrator
Role
Role Term: Text
research program
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01036260")
Topic
Neural networks (Computer science)
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01053693")
Topic
Parkinson's disease
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00872004")
Topic
Computational neuroscience
Language
Language Term: Text (ISO639-2B)
English
Origin Information
Date Created (keyDate="yes", encoding="w3cdtf")
2020
Note (displayLabel="Scholarly concentration")
Non-Scholarly Concentrator
Access Condition: use and reproduction (href="")
All rights reserved
Access Condition: logo (href="")
Identifier: DOI
10.26300/0236-vc19