Abstract
The ability to analyze and assimilate Electronic Medical Records (EMR) has great value to physicians, clinical researchers, and medical policy makers. Current EMR systems do not provide adequate support for fully exploiting the data. The growing size, complexity, and accessibility of EMRs demand a new set of tools for extracting knowledge of interest from the data. This paper presents an interactive visual mining solution for cohort study of EMRs. The basis of our design is multidimensional, visual aggregation of the EMRs. The resulting visualizations can help uncover hidden structures in the data, compare different patient groups, determine critical factors to a particular disease, and help direct further analyses. We introduce and demonstrate our design with case studies using EMRs of 14,567 Chronic Kidney Disease (CKD) patients.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 521-528 |
| Number of pages | 8 |
| ISBN (Print) | 9781479956692 |
| DOIs | |
| Publication status | Published - Dec 29 2014 |
| Event | 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 - Belfast, United Kingdom Duration: Nov 2 2014 → Nov 5 2014 |
Other
| Other | 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 |
|---|---|
| Country | United Kingdom |
| City | Belfast |
| Period | 11/2/14 → 11/5/14 |
Fingerprint
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics
Cite this
A visual analysis approach to cohort study of electronic patient records. / Wang, Chun Fu; Li, Jianping; Ma, Kwan Liu; Huang, Chih Wei; Li, Yu Chuan.
Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 521-528 6999214.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A visual analysis approach to cohort study of electronic patient records
AU - Wang, Chun Fu
AU - Li, Jianping
AU - Ma, Kwan Liu
AU - Huang, Chih Wei
AU - Li, Yu Chuan
PY - 2014/12/29
Y1 - 2014/12/29
N2 - The ability to analyze and assimilate Electronic Medical Records (EMR) has great value to physicians, clinical researchers, and medical policy makers. Current EMR systems do not provide adequate support for fully exploiting the data. The growing size, complexity, and accessibility of EMRs demand a new set of tools for extracting knowledge of interest from the data. This paper presents an interactive visual mining solution for cohort study of EMRs. The basis of our design is multidimensional, visual aggregation of the EMRs. The resulting visualizations can help uncover hidden structures in the data, compare different patient groups, determine critical factors to a particular disease, and help direct further analyses. We introduce and demonstrate our design with case studies using EMRs of 14,567 Chronic Kidney Disease (CKD) patients.
AB - The ability to analyze and assimilate Electronic Medical Records (EMR) has great value to physicians, clinical researchers, and medical policy makers. Current EMR systems do not provide adequate support for fully exploiting the data. The growing size, complexity, and accessibility of EMRs demand a new set of tools for extracting knowledge of interest from the data. This paper presents an interactive visual mining solution for cohort study of EMRs. The basis of our design is multidimensional, visual aggregation of the EMRs. The resulting visualizations can help uncover hidden structures in the data, compare different patient groups, determine critical factors to a particular disease, and help direct further analyses. We introduce and demonstrate our design with case studies using EMRs of 14,567 Chronic Kidney Disease (CKD) patients.
UR - http://www.scopus.com/inward/record.url?scp=84922824793&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84922824793&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2014.6999214
DO - 10.1109/BIBM.2014.6999214
M3 - Conference contribution
AN - SCOPUS:84922824793
SN - 9781479956692
SP - 521
EP - 528
BT - Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -