Paper Info
Title
Can we use big data to understand functional changes in swallowing, gait and handwriting?
Abstract
Summary form only given. A biomarker is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In this talk, I will present my efforts to develop computational biomarkers that can characterize temporal and spatial signatures (i.e., the unique patterns of moment-to-moment changes of physiologic variables under normal or pathologic conditions) and their relationship to other variables. Specifically, I will elaborate my efforts to develop computational biomarkers for detecting swallowing difficulties, gait changes and handwriting changes. These computational biomarkers are obtained by mining large data sets in order to characterize changes in the considered functional outcomes under various conditions.
Year
DOI
Venue
2017
10.1109/MECO.2017.7977118
2017 6th Mediterranean Conference on Embedded Computing (MECO)
Keywords
DocType
ISSN
Big Data,biologic processes,pathogenic processes,pharmacologic responses,therapeutic intervention,computational biomarkers,temporal signatures,spatial signatures,moment-to-moment changes,physiologic variables,normal conditions,pathologic conditions,swallowing difficulty detection,gait change detection,handwriting change detection,data set mining
Conference
2377-5475
ISBN
Citations 
PageRank 
978-1-5090-6743-5
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Ervin Sejdic114625.55