@article{(Open Science Index):https://publications.waset.org/pdf/8672, title = {Concepts Extraction from Discharge Notes using Association Rule Mining}, author = {Basak Oguz Yolcular}, country = {}, institution = {}, 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.}, journal = {International Journal of Computer and Information Engineering}, volume = {5}, number = {11}, year = {2011}, pages = {1276 - 1279}, ee = {https://publications.waset.org/pdf/8672}, url = {https://publications.waset.org/vol/59}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 59, 2011}, }