Evolutionary rule decision using similarity based associative chronic disease patients
- Authors
- Jung, Hoill; Yang, JungGi; Woo, Ji-In; Lee, Byung-Mun; Ouyang, Jinsong; Chung, Kyungyong; Lee, YoungHo
- Issue Date
- Mar-2015
- Publisher
- SPRINGER
- Keywords
- Data Mining; Clinical decision support system; Chronic disease patients; Telemedicine; U-Healthcare; IT convergence
- Citation
- CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.18, no.1, pp.279 - 291
- Journal Title
- CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
- Volume
- 18
- Number
- 1
- Start Page
- 279
- End Page
- 291
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10763
- DOI
- 10.1007/s10586-014-0376-x
- ISSN
- 1386-7857
- Abstract
- Efficient healthcare management has increasingly drawn much attention in healthcare sector along with recent advances in IT convergence technology. Population aging and a shift from an acute to a chronic disease with a long duration of illness have urgently necessitated healthcare service for efficient, systematic health management. Clinical decision support system (CDSS) is an integrated healthcare system that effectively guides health management and promotion, recommendation for regular health check-up, tailor-made diet therapy, health behavior change for self-care, alert service for drug interaction in patients with chronic diseases with a high prevalence. Although CDSS rule-based algorithm aids guidelines and decision making according to a single chronic disease, it is unable to inform unique characteristics of each chronic disease and suggest preventive strategies and guidelines of complex diseases. Therefore, this study proposes evolutionary rule decision making using similarity based associative chronic disease patients to normalize clinical conditions by utilizing information of each patient and recommend guidelines corresponding detailed conditions in CDSS rule-based inference. Decision making guidelines of chronic disease patients could be systematically established according to various environmental conditions using database of patients with different chronic diseases.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10763)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.