Commenced in January 2007
Paper Count: 1
Search results for: otorhinolaryngology
1 Concepts Extraction from Discharge Notes using Association Rule Mining
Authors: Basak Oguz Yolcular
Abstract:A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. In this study, we developed a domain based software system to transform 600 Otorhinolaryngology discharge notes to a structured form for extracting clinical data from the discharge notes. In order to decrease the system process time discharge notes were transformed into a data table after preprocessing. Several word lists were constituted to identify common section in the discharge notes, including patient history, age, problems, and diagnosis etc. N-gram method was used for discovering terms co-Occurrences within each section. Using this method a dataset of concept candidates has been generated for the validation step, and then Predictive Apriori algorithm for Association Rule Mining (ARM) was applied to validate candidate concepts.
Keywords: association rule mining, otorhinolaryngology, predictive apriori, text miningProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1489