Intelligent information retrieval lifecycle architecture based clustering genetic algorithm using SOA for modern medical industries
Naser El-Bathy, Ghassan M. Azar, Mohammed El-Bathy, Gordon Stein · 2011
Modernization of medical industries experiences numerous challenges. The modernization requires an innovative solution to determine diagnosis of diseases and the best treatment. This solution discovers related diseases to doctors' original diagnosis and quickly reassesses the situation if their diagnosis is incorrect. It also should eliminate unnecessary treatments and testing. It shortens time spent in hospitals for patients. This research, as reported in this paper focuses on creating such a solution in the form of an Intelligent Information Retrieval Lifecycle Architecture Based Clustering Extended Genetic Algorithm Using Service-Oriented Architecture (SOA). The purpose of the solution is to develop concepts and techniques based on the architecture to accelerate processing time of information retrieval at lower cost. The solution provides medical tasks that support strategic decision making and operational business processes. In a SOA environment, the study of this research develops new intelligent concepts of integrating approaches of search methodologies, information retrieval, clustering, genetic algorithm, and intelligent agents. A prototype is created and examined in order to validate the concepts.