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Tlemcen University at CELF eHealth 2018 Team Techno: Multilingual Information Extraction - ICD10 coding

We developed Naive Bayes (NB) classifier for text classification to information extraction from written text at CLEF eHealth 2018 challenge, task1. The data set used is called the CepiDC Causes of Death Corpus. It comprises French biomedical text reports of death causes. To extract ICD10 codes for each death certificate, a preprocessing process must be carried out, for example, we removed all terms from the certificates that are not related to medicine and after that we used a NB classifier to generate a classification model. The evaluation of the proposed approach does not show good performance compared with the results obtained by the other participants in the challenge.