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An Ontology Based Knowledge Preservation Model for Traditional Unani Medicines

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Brain Informatics and Health (BIH 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8609))

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Abstract

Traditional medicines can play a major role in global health care, due to its indigenous nature, easy access, and cost effectiveness. However, knowledge of this intellectual property is in danger of being lost. It is either undocumented or if documented, it is inaccessible and local in context. World Health Organization signifies the necessity to preserve and maintain this knowledge. Unani medicines, a subfield of traditional medicines, have been continuously practiced in Asia for about 2500 years, and it is facing the same situation of knowledge lost. To preserve knowledge of Unani medicines, initial kind of an effort has been done but a formal semantic structure, that is machine readable and reusable, is required to preserve this knowledge efficiently and effectively. This research focuses on conceptual structure of Unani medicines by presenting domain ontology which includes core principles and philosophy of Unani medicines, diseases, symptoms, diagnosis, drugs, and treatment. Knowledge about fundamentals is captured from expert interviews and books and then this knowledge is converted into ontologies using Protégé. Although it is not exhaustive domain ontology, however it may serve as a starting point for any knowledge based application of Unani medicines. In this research a semantic queries based case study along with a prototype expert system is also proposed.

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Amjad, S., Waheed, T., Enriquez, A.M.M., Aslam, M., Syed, A. (2014). An Ontology Based Knowledge Preservation Model for Traditional Unani Medicines. In: Ślȩzak, D., Tan, AH., Peters, J.F., Schwabe, L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science(), vol 8609. Springer, Cham. https://doi.org/10.1007/978-3-319-09891-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-09891-3_26

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09890-6

  • Online ISBN: 978-3-319-09891-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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