Ant inspired techniques in textual information retrieval from a hospital information system

摘要

In this work we have studied, evaluated and proposed different swarm intelligence techniques for mining information from loosely structured medical textual records with no apriori knowledge. In the paper we depict the process of mining a large dataset of ∼50,000–120,000 records × 20 attributes in database tables, originating from the hospital information system (thanks go to the University Hospital in Brno, Czech Republic) recording over 10 years. This paper concerns only textual attributes with free text input, that means 613,000 text fields in 16 attributes. Each attribute item contains ∼800–1,500 characters (diagnoses, medications, etc.). The output of this task is a set of orderedominal attributes suitable for rule discovery mining and automated processing.