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Practical approach for disease similarity calculation based on disease phenotype, etiology, and locational clues in disease names., , and . BIBM, page 1002-1009. IEEE Computer Society, (2016)Geometrical mapping of diseases with calculated similarity measure., , and . BIBM, page 1131-1134. IEEE Computer Society, (2017)UD_Japanese-CEJC: Dependency Relation Annotation on Corpus of Everyday Japanese Conversation., , , and . SIGDIAL, page 324-335. Association for Computational Linguistics, (2023)UD-Japanese BCCWJ: Universal Dependencies Annotation for the Balanced Corpus of Contemporary Written Japanese., and . UDW@EMNLP, page 117-125. Association for Computational Linguistics, (2018)Discriminating between Relevant and Irrelevant Text for Fact Validation., , , , and . NTCIR, National Institute of Informatics (NII), (2014)Universal Dependencies Version 2 for Japanese., , , , , , , , and . LREC, European Language Resources Association (ELRA), (2018)Incorporating Unsupervised Features into CRF based Named Entity Recognition., , and . NTCIR, National Institute of Informatics (NII), (2014)Disease Similarity Calculation on Simplified Disease Knowledge Base for Clinical Decision Support Systems., , and . FLAIRS, page 501-506. AAAI Press, (2015)KitAi: Textual Entailment Recognition System for NTCIR-10 RITE2., , , and . NTCIR, National Institute of Informatics (NII), (2013)Cost decisions in the development of disease knowledge base : A case study., , , , , and . BIBM, page 62-69. IEEE Computer Society, (2014)