Journal of the American Society for Information Science
An interactive system for finding complementary literatures: a stimulus to scientific discovery
Artificial Intelligence - Special issue on scientific discovery
Fast discovery of association rules
Advances in knowledge discovery and data mining
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We present an interactive discovery support system, which for a given starting concept of interest, discovers new, potentially meaningful relations with other concepts that have not been published in the medical literature before. The known relations between the medical concepts come from the MEDLINE bibliographic database and the UMLS (Unified Medical Language System). We use association rules to mine for the relationships between medical concepts. Then we demonstrate a successful application of the system for predicting a gene candidate for a disease, a fact recently confirmed via the positional cloning approach. We conclude that the discovery support system we developed is a useful tool, complementary to the already existing bioinformatic tools in the field of human genetics. The system described in this chapter is available at http://www.mf.uni-lj.si/bitola/