World J Plast Surg. 2014 Jul;3(2):87-92
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.
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