Report on the NTCIR-12 MedNLPDoc Task Results
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چکیده
The reuse of clinical data for the research environment is becoming one of the important tasks in medical informatics. The automatic assignment of the medical codes to the pre-identified concepts is turning to the Sisyphean task. For the MedNLP task in NTCIR-12 a new approach to automatically enrich the dictionary using online data is proposed. We have developed a text-mining system able to treat medical textual data represented in Japanese language and assign ICD-10 codes with English descriptors to the identified concepts. There are three main parts in the functionality of the system: 1) English version of ICD-10-based dictionary, 2) Wikipedia-based synonyms 3) statistical translation tools such Yandex and Google Translate APIs. This report presents the description of the system and the achieved results on the MedNLPDoc test data. Additionally, we provide an ICD assignation frequency in University Hospitals of Geneva. General Terms Algorithms, Standardization, Languages, Theory, Legal Aspects
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تاریخ انتشار 2016