Document Type
Report
Publication Date
3-2013
Abstract
Most of the existing approaches for detecting diseases/risk score form observations (sensor and textual) ignore the presence of any prior knowledge of the disease. In this work, we start top-down by enumerating the symptoms of Parkinson's Disease (PD) and map the symptoms to its possible manifestations in sensor observations (bottom-up). We show such manifestations and further use these manifestations as features to build classifiers to differentiate between the PD patients and the control group.
Repository Citation
Anantharam, P.,
Thirunarayan, K.,
Taslimi, V.,
& Sheth, A. P.
(2013). Predicting Parkinson's Disease Progression with Smartphone Data. .
https://corescholar.libraries.wright.edu/knoesis/569
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Submitted to the Parkinson's disease challenge sponsored by The Michael J. Fox Foundation for Parkinson's Research, March, 2013.