loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Si-Chi Chin 1 ; Kiyana Zolfaghar 1 ; Senjuti Basu Roy 1 ; Ankur Teredesai 1 and Paul Amoroso 2

Affiliations: 1 Institute of Technology and The University of Washington - Tacoma, United States ; 2 Multicare Health System, United States

ISBN: 978-989-758-010-9

Keyword(s): Hospital Readmission Risk Prediction, Discretization, Data Exploration.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Management and Quality ; Data Manipulation ; Data Mining ; Data Visualization ; Databases and Information Systems Integration ; Datamining ; Decision Support Systems ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Insightful and principled visualization techniques may successfully help complex clinical data exploration tasks and aid in the process of knowledge discovery. In this paper, we propose a framework Divide-n-Discover to visualize and explore clinical data effectively, and demonstrate its effectiveness in predicting readmission risk for Congestive Heart Failure patients. Our proposed method provides clinicians a mechanism to dynamically explore the data and to understand how a single factor may influence the risk of readmission for a given patient. For example, our study indicates that patients between age 47 and 48 have 2.63 time higher chance of getting readmitted to the hospital within 30 days, compared to other patients; likewise, patients with length of stay above 13 days are 2.27 times more likely to be readmitted within 30 days. The finding suggests that hospitals might be under pressure to discharge patients within two week while some patients may benefit from a longer stay. These observations may become valid hypotheses leading to further clinical investigation or discoveries. To the best of our knowledge, this is the first ever work that proposes principled discretization and visualization techniques in the hospital readmission risk prediction problem. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.198.86.28

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Chin S., Zolfaghar K., Basu Roy S., Teredesai A. and Amoroso P. (2014). Divide-n-Discover - Discretization based Data Exploration Framework for Healthcare Analytics.In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014) ISBN 978-989-758-010-9, pages 329-333. DOI: 10.5220/0004802403290333

@conference{healthinf14,
author={Si-Chi Chin and Kiyana Zolfaghar and Senjuti Basu Roy and Ankur Teredesai and Paul Amoroso},
title={Divide-n-Discover - Discretization based Data Exploration Framework for Healthcare Analytics},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)},
year={2014},
pages={329-333},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004802403290333},
isbn={978-989-758-010-9},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)
TI - Divide-n-Discover - Discretization based Data Exploration Framework for Healthcare Analytics
SN - 978-989-758-010-9
AU - Chin S.
AU - Zolfaghar K.
AU - Basu Roy S.
AU - Teredesai A.
AU - Amoroso P.
PY - 2014
SP - 329
EP - 333
DO - 10.5220/0004802403290333

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.