Overview of an agent-based IDSS framework for neonatal analysis and trend detection

![CDATA[This paper aims to demonstrate the feasibility of using an Agent-Based Intelligent Decision Support System (IDSS) Framework for Neonatal Analysis and Trend Detection particularly in the areas of extensiveness and adaptability. The research into agent-based intelligent decision support systems is important to the medical industry because these systems can be used to improve the quality of healthcare in many ways. The areas these systems can be used in are diverse from the storage of medical records to the examination and evaluation of real-time data gathered from monitors. Such systems are helpful to doctors and nurses in the diagnosis and treatment of patient with a wide variety of conditions. The paper presents a framework representing part of the e-Baby architecture that is under development as part of the e-Baby collaborative research project. The paper also overviews a survey of existing agent-based IDSS in the medical industry. Once implemented the system will be tested for clinical impact however at this stage the major focus is on its extensibility and adaptability for detecting trends and patterns in clinical data. An Agent-Based IDSS Framework for Neonatal Analysis and Trend Detection is also presented. At this stage of the research we have placed a Data Collection Unit (DCU) at Nepean Hospital's NICU. Combining all the features provided by the multiple components together with the features that were noted earlier as being required in the framework such as real-time data mining and being a Clinical Research system, and this framework will be both comprehensive and extremely adaptable.]]