@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},