Decision Support System for Hepatitis Disease Diagnosis using Bayesian Network

  • Shamshad Lakho Department of Information Technology, Quaid-e-Awam University of Engineering, Science & TechnologyNawabshah, Pakistan
  • Akhtar Hussain Jalbani Department of Information Technology, Quaid-e-Awam University of Engineering, Science & Technology Nawabshah, Pakistan
  • Muhammad Saleem Vighio Department of Information Technology, Quaid-e-Awam University of Engineering, Science & Technology Nawabshah, Pakistan
  • Imran Ali Memon Department of Information Technology, Shaheed Benazir Bhutto University, SBA Nawabshah, Pakistan
  • Saima Siraj Soomro Department of Information Technology, Quaid-e-Awam University of Engineering, Science & Technology Nawabshah, Pakistan
  • Qamar-un-Nisa Soomro Department of Examination, Quaid-e-Awam University of Engineering, Science & Technology Nawabshah, Pakistan

Abstract

Medical judgments are tough and challenging as the decisions are often based on the deficient and ambiguous information. Moreover, the result of decision process has direct effects on human lives. The act of human decision declines in emergency situations due to the complication, time limit, and high risks. Therefore, provision of medical diagnosis plays a dynamic role, specifically in the preliminary stage when a physician has limited diagnosis experience and identifies the directions to be taken for the treatment process. Computerized Decision Support Systems have brought a revolution in the medical diagnosis. These automatic systems support the diagnosticians in the course of diagnosis. The major role of Decision Support Systems is to support the medical personnel in decision-making procedures regarding disease diagnosis and treatment recommendation. The proposed system provides easy support in Hepatitis disease recognition. The system is developed using the Bayesian network model. The physician provides the input to the system in the form of symptoms stated by the patient. These signs and symptoms match with the casual relationships present in the knowledge model. The Bayesian network infers conclusion from the knowledge model and calculates the probability of occurrence of Hepatitis B, C and D disorders.

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Published
2017-12-31
How to Cite
LAKHO, Shamshad et al. Decision Support System for Hepatitis Disease Diagnosis using Bayesian Network. Sukkur IBA Journal of Computing and Mathematical Sciences, [S.l.], v. 1, n. 2, p. 11-19, dec. 2017. ISSN 2522-3003. Available at: <http://journal.iba-suk.edu.pk:8089/SIBAJournals/index.php/sjcms/article/view/51>. Date accessed: 17 nov. 2018. doi: https://doi.org/10.30537/sjcms.v1i2.51.
Section
Research Articles