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Geriatric Disease Reasoning Based on Knowledge Graph

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Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health (CyberDI 2019, CyberLife 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1138))

Abstract

The lack of health care for ageing has become one of China’s most serious challgengs. The main work of this paper is building a database of a geriatric knowledge graph and proposing three inference rules based on Bayesian algorithm, which can effectively help the elderly to understand their health better and find out the abnormal condition as soon as possible. At the same time, it can assist doctors make auxiliary medical decisions and improve the cure rate. This article introduced a complete process of building a knowledge graph, from schema structure design to data acquisition, and processing the data until it fits the standard. Before applying to disease reasoning, we imported knowledge data into the Neo4j graph database to make full use of the inference flexibility and accuracy of the knowledge graph.

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Shaobin Feng & Huansheng Ning

  2. School of Reliability and Systems Engineering, Beihang University, Beijing, 100191, China

    Shunkun Yang

  3. College of Economic and Management, China Agriculture University, Beijing, 100083, China

    Dongmei Zhao

Authors
  1. Shaobin Feng
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  2. Huansheng Ning
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  3. Shunkun Yang
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  4. Dongmei Zhao
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Corresponding author

Correspondence to Dongmei Zhao .

Editor information

Editors and Affiliations

  1. University of Science and Technology, Beijing, China

    Huansheng Ning

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© 2019 Springer Nature Singapore Pte Ltd.

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Feng, S., Ning, H., Yang, S., Zhao, D. (2019). Geriatric Disease Reasoning Based on Knowledge Graph. In: Ning, H. (eds) Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. CyberDI CyberLife 2019 2019. Communications in Computer and Information Science, vol 1138. Springer, Singapore. https://doi.org/10.1007/978-981-15-1925-3_33

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  • DOI: https://doi.org/10.1007/978-981-15-1925-3_33

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1924-6

  • Online ISBN: 978-981-15-1925-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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