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    A Generic Knowledge Based Medical Diagnosis Expert System

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    A_Generic_Knowledge_Based_Medical_Diagnosis_Expert_System.pdf
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    PDF
    Description:
    Accepted manuscript
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    Type
    Conference Paper
    Authors
    Huang, Xin
    Tang, Xuejiao
    Zhang, Wenbin
    Zhang, Ji
    Zhang, Mingli
    Gan, Wensheng
    Pei, Shichao
    Liu, Zhen
    Huang, Yiyi
    KAUST Department
    Computer Science
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2021-12-30
    Online Publication Date
    2021-12-30
    Print Publication Date
    2021-11-29
    Permanent link to this record
    http://hdl.handle.net/10754/675047
    
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    Abstract
    In this paper, we design and implement a generic medical knowledge based system (MKBS) for identifying diseases from several symptoms. In this system, some important aspects like knowledge bases system, knowledge representation, inference engine have been addressed. The system asks users different questions and inference engines will use the certainty factor to prune out low possible solutions. The proposed disease diagnosis system also uses a graphical user interface (GUI) to facilitate users to interact with the expert system. Our expert system is generic and flexible, which can be integrated with any rule bases system in disease diagnosis.
    Citation
    Huang, X., Tang, X., Zhang, W., Zhang, J., Zhang, M., Gan, W., … Huang, Y. (2021). A Generic Knowledge Based Medical Diagnosis Expert System. The 23rd International Conference on Information Integration and Web Intelligence. doi:10.1145/3487664.3487728
    Sponsors
    This work was supported by a NVIDIA GPU Grant.
    Publisher
    ACM
    Conference/Event name
    23rd International Conference on Information Integration and Web Intelligence, iiWAS 2021
    ISBN
    9781450395564
    DOI
    10.1145/3487664.3487728
    arXiv
    2110.04439
    Additional Links
    https://dl.acm.org/doi/10.1145/3487664.3487728
    ae974a485f413a2113503eed53cd6c53
    10.1145/3487664.3487728
    Scopus Count
    Collections
    Conference Papers; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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