Volume 3, Issue 2 (7-2014)                   wjps 2014, 3(2): 87-92 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Salehahmadi Z, Manafi A. How Can bee Colony Algorithm Serve Medicine?. wjps. 2014; 3 (2) :87-92
URL: http://wjps.ir/article-1-110-en.html
Department of Information Technology, Bushehr University of Medical Sciences, Bushehr, Iran
Abstract:   (9456 Views)
Healthcare professionals usually should make complex decisions with far reaching consequences and associated risks in health care fields. As it was demonstrated in other industries, the ability to drill down into pertinent data to explore knowledge behind the data can greatly facilitate superior, informed decisions to ensue the facts. Nature has always inspired researchers to develop models of solving the problems. bee colony algorithm (BCA), based on the self-organized behavior of social insects is one of the most popular member of the family of population oriented, nature inspired meta-heuristic swarm intelligence method which has been proved its superiority over some other nature inspired algorithms. The objective of this model was to identify valid novel, potentially useful, and understandable correlations and patterns in existing data. This review employs a thematic analysis of online series of academic papers to outline BCA in medical hive, reducing the response and computational time and optimizing the problems. To illustrate the benefits of this model, the cases of disease diagnose system are presented.
Full-Text [PDF 288 kb]   (2041 Downloads)    
Type of Study: Original Article | Subject: Special
Received: 2014/05/14 | Accepted: 2014/05/14 | Published: 2014/05/14

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


© 2020 All Rights Reserved | World Journal of Plastic Surgery

Designed & Developed by : Yektaweb