Emergency Departments (ED) in a hospital is a complex unit where the fight between life and death is always in a breathing time. The ED has been frustrated by the problem of overcrowding and long time waiting for over decades. With the development of computer technology, various kinds of information systems have appeared and make people work more effectively. Emergency Department Information Systems (EDIS) have been heralded as a “must” for the modern ED and using of the EDIS can enhance patients care, decrease the waiting time, and reduce the situation of overcrowding. Data mining techniques has been using in medical researches for many years and has been found to be quite effective. The objective of this paper is to design the collaborative intelligence for interactive diagnosis systems as part of EDIS. Based on the patients flow in the ED, we utilize data mining techniques to generate predictive models to help physicians make diagnosis faster and more accurately. By using this decision-supporting system, physicians can work more effectively and the waiting times in ED can decrease.
['Sung Ho Ha', 'Zhenyu Zhang']
Collaborative Intelligence for Intelligent Diagnosis Systems in Hospital Environment