Agent paradigm in clinical large-scale data mining environment
A. Ouali, Zhor Ramdane-Cherif, Amar Ramdane-Chérif, Nicole Lévy, Marie‐Odile Krebs · 2004
Intelligent agents are new paradigm for developing software applications. More than this, agent-based computing has been hailed as the next significant breakthrough in software development and the new revolution in classification techniques for large-scale data mining environment. Currently, agents are the focus of intense interest on the part of many sub-fields of computer science and artificial intelligence. In our work, we develop multi-agents platform gathering different type of agents. We provide to this platform the ability to operate automatically thanks to autonomous and intelligent agents. This new technology combines the agent approach with the monitoring strategy in order to automatically use the data mining for clinical analysis. Research into data mining in medical diagnosis is important to guide the clinicians in different phases of their diagnostic evaluations. The platform offers an interesting tool for data mining analysis using graph outputs and measures. An implementation of this platform on clinical database is presented. We discuss the importance of our approach and how it supports the data mining and also the possibility to generate and evaluate several association rules according to some scenarios predefined in the intelligent knowledge base of the proposed platform.