%0 Journal Article
	%A Basak Oguz Yolcular
	%D 2011
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 59, 2011
	%T Concepts Extraction from Discharge Notes using Association Rule Mining
	%U https://publications.waset.org/pdf/8672
	%V 59
	%X 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.
	%P 1276 - 1279