Paper Info
Title
VisAGE: Integrating external knowledge into electronic medical record visualization.
Abstract
In this paper, we present VisAGE, a method that visualizes electronic medical records (EMRs) in a low-dimensional space. Effective visualization of new patients allows doctors to view similar, previously treated patients and to identify the new patients' disease subtypes, reducing the chance of misdiagnosis. However, EMRs are typically incomplete or fragmented, resulting in patients who are missing many available features being placed near unrelated patients in the visualized space. VisAGE integrates several external data sources to enrich EMR databases to solve this issue. We evaluated VisAGE on a dataset of Parkinson's disease patients. We qualitatively and quantitatively show that VisAGE can more effectively cluster patients, which allows doctors to better discover patient subtypes and thus improve patient care.
Year
Venue
Keywords
2018
Biocomputing-Pacific Symposium on Biocomputing
Electronic medical records,Data integration,Knowledge graphs,Visualization
Field
DocType
Volume
Data science,Data integration,Protein Interaction Map,Knowledge graph,Visualization,Disease progression,Human–computer interaction,Medical record,Bioinformatics,Computer graphics,Medicine
Conference
23
ISSN
Citations 
PageRank 
2335-6936
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Edward Huang122.39
Sheng Wang2498.26
ChengXiang Zhai311908649.74