Comparative assessment of rule-based and Bayes' theorem as inference engines in diagnosing symptoms for Islamic medication expert system

Daud, H. and Razali, R. and Low, T.J. and Sabdin, M. and Zafrul, S.Z.M. (2014) Comparative assessment of rule-based and Bayes' theorem as inference engines in diagnosing symptoms for Islamic medication expert system. In: UNSPECIFIED.

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Abstract

An expert system for diagnosing sickness and suggesting treatment based on Islamic Medication (IM) was constructed using Rule Based (RB) and Bayes' theorem (BT) algorithms independently as its inference engine. Comparative assessment on the quality of diagnosing based on symptoms provided by users for certain type of sickness using RB and BT reasoning that lead to the suggested treatment (based on IM) are discussed. Both approaches are found to be useful, each has its own advantages and disadvantages. Major difference of the two algorithms is the selection of symptoms during the diagnosing process. For BT, likely combinations of symptoms need to be classified for each sickness before the diagnosing process. This eliminates any irrelevant sickness based on the combination of symptoms provided by user and combination of symptoms that is unlikely. This is not the case for RB, it will diagnose the sickness as long as one the symptoms is related to the sickness regardless of unlikely combination. Few tests have been carried out using combinations of symptoms for same sickness to investigate their diagnosing accuracy in percentage. BT gives more promising diagnosing results compared to RB for each sickness that comes with common symptoms. © 2014 AIP Publishing LLC.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 1; Conference of 3rd International Conference on Mathematical Sciences, ICMS 2013 ; Conference Date: 17 December 2013 Through 19 December 2013; Conference Code:106205
Uncontrolled Keywords: Inference engines, Bayes theorem; Comparative assessment; Islamic Medication; Rule based, Diseases
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:16
Last Modified: 09 Nov 2023 16:16
URI: https://khub.utp.edu.my/scholars/id/eprint/5144

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