ICD9-based Text Mining Approach to Children Epilepsy Classification

摘要: Abstract According with the World Health Organization, around 50 million people in world have epilepsy. After diagnosis process, physicians classify epilepsy according to International Classification of Diseases, Ninth Revision (ICD-9). Often exams as electroencephalograms and magnetic resonances are used create a more accurate short amount time. The classification process is time consuming demands realization complementary exams. To circumvent this laborious we propose an automatic classifying epileptic diagnoses based on ICD-9. We put forward text mining approach, using processed electronic medical records K-Nearest Neighbor applied white-box multi classifier approach each instance mapping into corresponding standard code. Results suggests good performance proposing from records, despite reduced volume available training data.