Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures-Reference-Cited by-同舟云学术

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures

Published:2016-08-08 Issue:9 Volume:31 Page:1314-1326
ISSN:0885-3185
Container-title:Movement Disorders
language:en
Short-container-title:Mov Disord.

Author:

Kubota Ken J.¹,Chen Jason A.²³,Little Max A.⁴⁵

Affiliation:

1. Department of Data Science; tranSMART Foundation; Wakefield Massachusetts USA

2. Verge Genomics; San Francisco California USA

3. Interdepartmental Program in Bioinformatics; University of California at Los Angeles; Los Angeles California USA

4. Aston University; Aston Triangle Birmingham United Kingdom

5. Media Lab; Massachusetts Institute of Technology; Cambridge Massachusetts USA

Publisher

Wiley

Subject

Neurology (clinical),Neurology

Reference43 articles.

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3. Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): Process, format, and clinimetric testing plan;Goetz;Mov Disord,2007

4. Smartphone-PD: Preliminary results of an mHealth application to track and quantify characteristics of Parkinson's disease in real-time (Abstracts of the Nineteenth International Congress of Parkinson's Disease and Movement Disorders);Abiola;Mov Disord,2015

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