DocumentCode :
3705621
Title :
TimeStitch: Interactive multi-focus cohort discovery and comparison
Author :
Peter J. Polack; Shang-Tse Chen; Minsuk Kahng; Moushumi Sharmin; Duen Horng Chau
Author_Institution :
Georgia Tech., USA
fYear :
2015
Firstpage :
209
Lastpage :
210
Abstract :
Whereas event-based timelines for healthcare enable users to visualize the chronology of events surrounding events of interest, they are often not designed to aid the discovery, construction, or comparison of associated cohorts. We present TimeStitch, a system that helps health researchers discover and understand events that may cause abstinent smokers to lapse. TimeStitch extracts common sequences of events performed by abstinent smokers from large amounts of mobile health sensor data, and offers a suite of interactive and visualization techniques to enable cohort discovery, construction, and comparison, using extracted sequences as interactive elements. We are extending TimeStitch to support more complex health conditions with high mortality risk, such as reducing hospital readmission in congestive heart failure.
Keywords :
"Electronic mail","Data mining","Cloning","Medical services","Mobile communication","Data visualization","Heart"
Publisher :
ieee
Conference_Titel :
Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on
Type :
conf
DOI :
10.1109/VAST.2015.7347682
Filename :
7347682
Link To Document :
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