CASE-BASED REASONING IN IVF - PREDICTION AND KNOWLEDGE MINING

In vitro fertilization (IVF) is a medically-assisted reproduction tech nique, enabling infertile couples to achieve successful pregnancy. Giv en the unpredictability of the task, we propose to use a case-based re asoning system that exploits past experiences to suggest possible modi fications to an NF treatment plan in order to improve overall success rates. Once the system's knowledge base is populated with a sufficient number of past cases, it can be used to explore and discover interest ing relationships among data, thereby achieving a form of knowledge mi ning. The article describes the TA3(IVF) system-a case-based reasoning system which relies on context-based relevance assessment to assist i n knowledge visualization, interactive data exploration and discovery in this domain. The system can be used as an advisor to the physician during clinical work and during research to help determine what knowle dge sources are relevant for a treatment plan. (C) 1998 Elsevier Scien ce B.V.