Abstract
With the development of information technology, a large amount of information data has been accumulated in the field of obstetric. The effective ways to manage and apply these data are to construct a professional medical knowledge graph. In this paper, the Chinese Obstetric Knowledge Graph (COKG) based on multiple data sources of the obstetric professional thesauruses, clinical pathways, diagnosis, and treatment norms is constructed by the semi-automated method. The framework of concept classification and the related description are established. Thus COKG conceptual layer is also built. Based on traditional models of BI-LSTM-CRF and PCNN, and the guidance of medical experts, the data layer of COKG was founded by more than 2 million unstructured text words via artificially calibrating. Finally, COKG, which included 2343 diseases and 15249 named entity relationships, is constructed by knowledge fusion of multi-source data. The constructed COKG can provide structured knowledge support for medical question-answering systems, intelligent assisted diagnosis and treatment.
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Acknowledgments
We thank the anonymous reviewers for their constructive comments, and gratefully acknowledge the support of National Key Research and Development Program (2017YFB1002101), National Social Science Foundation Major Project (17ZDA138), National Natural Science Foundation of China (62006211), China Postdoctoral Science Foundation Funding Project (2019TQ0286, 2020M682349), Henan Science and Technology Research Project (192102210260), Henan Medicine Science and Technology Research Plan: Provincial and Ministry Co-construction Project (SB201901021), Henan Provincial Key Scientific Research Project of Colleges and Universities (19A520003, 20A520038), Ministry of Education Humanities and Social Science Planning Project (20YJA740033), Henan Province Philosophy and Social Science Planning Project (2019BYY016).
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Zhang, K., Hu, C., Song, Y., Zan, H., Zhao, Y., Chu, W. (2022). Construction of Chinese Obstetrics Knowledge Graph Based on the Multiple Sources Data. In: Dong, M., Gu, Y., Hong, JF. (eds) Chinese Lexical Semantics. CLSW 2021. Lecture Notes in Computer Science(), vol 13250. Springer, Cham. https://doi.org/10.1007/978-3-031-06547-7_31
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