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A Fibrosis Diagnosis Clinical Decision Support System Using Fuzzy Knowledge

  • Research Article - Computer Engineering and Computer Science
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Abstract

Liver cirrhosis, the end stage of chronic liver disease, is one of the major risk factors for the development of liver cancer, and may result in premature death. This research proposes a fuzzy fibrosis decision support (F2DS) system. It is a fuzzy knowledge-based expert system for liver fibrosis stage prediction. F2DS is carefully based on a set of knowledge acquisition and machine learning techniques. In addition, the system depends on domain expert knowledge for designing the membership functions and validating the fuzzy knowledge base. It depends on a suitable list of 17 symptoms, and laboratory test features that can accurately and significantly describe fibrosis patients. The experimental results of the expert system were obtained using a real dataset from the Liver Institute, Mansoura University, Egypt, of 119 patients infected by chronic viral hepatitis C. The performance of the system was evaluated with many metrics, achieving a testing accuracy of 95.7%. The evaluation of proposed fuzzy expert system shows its capability of diagnosing the stages of liver fibrosis with a high degree of accuracy, and it can be embedded as a component in a healthcare system to assist physicians in their daily practice. In addition, students training in medicine can benefit from this system.

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Authors and Affiliations

  1. Information Systems Department, Faculty of Computers and Information Sciences, Mansoura University, Mansoura, Egypt

    Sara Sweidan & Hazem El-Bakry

  2. Faculty of Computers & Informatics, Benha University, Benha, Egypt

    Shaker El-Sappagh & Sahar Sabbeh

  3. Department of Information and Communication Engineering, Inha University, Incheon, South Korea

    Shaker El-Sappagh & Kyung-Sup Kwak

  4. Faculty of Computing and Information Technology, University of Jeddah, Jeddah, Saudi Arabia

    Sahar Sabbeh

  5. Faculty of Pharmacy, Mansoura University, Mansoura, Egypt

    Farid A. Badria

Authors
  1. Sara Sweidan
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  2. Shaker El-Sappagh
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  3. Hazem El-Bakry
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  4. Sahar Sabbeh
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  5. Farid A. Badria
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  6. Kyung-Sup Kwak
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Correspondence to Sara Sweidan.

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Sweidan, S., El-Sappagh, S., El-Bakry, H. et al. A Fibrosis Diagnosis Clinical Decision Support System Using Fuzzy Knowledge. Arab J Sci Eng 44, 3781–3800 (2019). https://doi.org/10.1007/s13369-018-3670-8

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  • DOI: https://doi.org/10.1007/s13369-018-3670-8

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