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AZERYNA ANAK MIKE (35555)

Introduction
People seek mechanics when they encounter cars problem. Plus, people also seek
doctors when they feel unwell or sick. These people are identified as human expert as they
are expertise in their specific area. Due to increasing of population of human in the world,
some of the needs cannot be fulfilled due to less human expert.
Thus, a knowledge based system was introduced. Piatti, Antonucci and Zaffalon
(2010) defined knowledge based systems (KBS) as an application developed in computer that
have the same level of human expert in a specific domain. Expert system (ES) or knowledge
based system consists of a knowledge base and the reasoning engine (Tripathi, 2011).
KBS is sort of a replica of the human expert. Dragulescu and Albu (2007) stated that
KBS does not take over the human expert but assist them. Why is that so? This is because the
human experts may have problem while helping their customers such as fatigue, stress and so
on (Dragulescu & Albu, 2007). The advantages of KBS are the knowledge representation that
used was easy to understand, direct approaches and the system can be enforced orderly
(Sadeghian & Lavers, 2004).
Knowledge engineering is a process of building the system (Piatti, Antonucci &
Zaffalon, 2010). The knowledge engineer will take important role in this process. They
acquire the expert knowledge and build a KBS based on it. The belief that an expert holds is
actually expert knowledge (Piatti, Antonucci & Zaffalon, 2010). Based on Piatti, Antonucci
and Zaffalon (2010), they mentioned that knowledge engineer must choose a mathematical
formalism when building it to show the expert knowledge.
Medical field
Dimitrios (2012) wrote that to build a health system, more knowledge from medical,
engineering and technology fields are wanted by the managements. He also stated that the
importance of information of human, material and financial in are worsen as the time passes
(Dimitrios, 2012). Yang, Li and Liu (2011) stated that due to increasing number of patients
that need best and inexpensive medical treatment has become the center objective of medical
industry to improve their services.

AZERYNA ANAK MIKE (35555)
Thus a medical expert system is produced. Based on Li, Xu and Chen (2012), medical
expert system is a computer program that fuse basis knowledge of medical, inference steps
and control strategy. A thorough medical expert system should consist of knowledge base,
database, inference engine, knowledge acquisition module and interface (Li, Xu & Chen,
2012). Beforehand, the knowledge engineer must make sure that the knowledge acquired is
easy to compute and store. All the storage will take place in the database.
Application of expert system in medical diagnosis
In this paper, two medical KBS that are been focused on:
Hepatitis Diagnosis using Artificial Neural Networks.
In Dragulescu and Albu’s paper (2007), they stated that this KBS was used to provide
a guess about patients that have been affected by the virus which is hepatitis virus. They
mentioned that the chance taken for the patients to recover increase if a correct analysis and
enough treatment are provided.
Detection of Mental Disorder
Windriyani, Wiharto and Sihwi (2013) stated that this system is a diagnostic system to
identify a psychiatrist patient. This is due the number of residents with mental disorders are
increasing but less number of psychiatrists detected.
Type of knowledge and knowledge acquisition
1. Type of knowledge
These applications used domain knowledge. Based on Sajja and Akerkar
(2010), domain knowledge is truth knowledge in a particular area that
acquired from specialists and the experts.


Hepatitis Diagnostic: expert’s knowledge of hepatitis is acquired then
store to be the reference of the doctor.



Detection of mental disorder: build by retrieve the expert’s knowledge,
psychiatrist as the knowledge of the expert system (Windriyani,
Wiharto & Sihwi, 2013).

AZERYNA ANAK MIKE (35555)
2. Knowledge acquisition
This process is done by the knowledge engineer. He needs to acquire the
domain knowledge and thus build and store it in storage. This process involves
knowledge elicitation, knowledge representation and knowledge execution.


Hepatitis Diagnostic: It uses logical and statistical inference in this
system (Dragulescu & Albu, 2007). The knowledge is collected from
the experts.

In logical inference, it uses rule based method to

implement and represent human expert reasoning (Dragulsecu & Albu,
2007).


Detection of mental disorder: The knowledge is collected through
interviews with the experts (Windriyani, Wiharto & Sihwi, 2013).
Here, many experts are used thus the knowledge are combined. The
representation of the knowledge involved design the base of
knowledge, decision tables, decision tree and forward chaining
inference analysis. It uses rule based method to represent the data. It
also uses forward chaining to execute the process.

AZERYNA ANAK MIKE (35555)
Approaches in designing the systems
The knowledge engineer wills deciding on which approaches he will use to design the
system. These two applications use cyclical development approach. It is an iterative process
of designing the systems. First step is knowledge acquisition where the knowledge is
obtained by the knowledge engineer. Then, he will plans on how he would like to represent
the data in more understandable knowledge. Next, he will do prototype development and
present it to the expert. Thus, the expert will comment or critique the prototype until it
satisfied the expert by displaying the correct knowledge to the users.

Prototype
development

Figure 1. Prototype at an early Stage, in West African Journal of Industrial & Academic
Research, retrieved from www.ajol.info/index.php/wajiar/article/download/114994/104618.
Copyright 2014 by West African Journal of Industrial & Academic Research.
Figure 1. Flag of Maldova. From Moldova, [Flag], in Encyclopedia Britannica, retrieved from
http://www.britannica.com/EBchecked/media/62190/. Copyright 2012 by Encyclopedia Britannica.

Further improvement of the systems
Instead of rule based system, they can use other method such as semantic networks in
diagnosis. Rule based system used Booelan algorithm which consists 1 or 0. It limits the
reasoning. Widening the reasoning can improve the system better.

AZERYNA ANAK MIKE (35555)
Acquire the knowledge from other resources instead of expert to add in more can be a helpful
improvement to the system as it does not limit to the expert only. They can acquire from
documents or so on.

AZERYNA ANAK MIKE (35555)
References
Chen, W., Liu, X., Liu, Y., & Fang, Y. (2006). A machine learning algorithm for expert
system based on mycin model. Computer Engineering and Technology, 2, 262-265.
Dimitrios, K. (2012). Knowledge based management in health system. Review of
International Comparative Management, 13(2), 284-293.
Dragulescu, D., & Albu, A. (2007). Expert system for medical predictions. IEEE 4th
International Symposium on Applied Computational Intelligence and Informatics, 123-128.
Ele, S., Umoh, E., & Adesola, W. (2014). An overview of the development principles, stages
and building blocks of expert system. West African Journal of Industrial & Academic
Research, 11(1), 44-58.
Li, X., Xu, Q., & Chen, J. (2010). Research of the medical expert system under a new
architecture. Industrial Mechatronics and Automation (ICIMA)(244-247). China: IEEE.
Piatti, A., Antonucci, A., & Zaffalon, M. (2010). Building knowledge-based systems by
creedal networks: A tutorial. Nova Science, 0.
Peleg, M., & Samson, T. (2006). Decision support, knowledge representation and
management in medicine. Yearb Med Inform, 45, 72-80.
Saheghian, A., & Lavers, J. (2004). Implementation ok knowledge-based system for iron core
inductor design. IEEE Transactions of Magnetics, 40(6), 3495-3504.
Sajja, P. S., & Akerkar, R. (2010). Advanced knowledge based systems, model application
and research. Retrieved from http://www.tmrfindia.org/eseries/ebookv1-c1.pdf
Tripathi, K. (2011). A review on knowledge-based expert system: Concept and architecture.
IJCA Special Issue on “Artificial Intelligence Techniques - Novel Approaches & Practical
Applications”, 4, 19-23.
Windriyani, P., Wiharto, &Sihwi, S. (2013). Expert system for detecting mental disorder with
forward chaining method. ICT for Smart Society, 2013 International Conference, 1-7.
Yang, H., Li, W., & Liu, K. (2012). Knowlegde-based clinical pathway for medical quality
improvement. Inf Syst Front, 14, 105-117.

AZERYNA ANAK MIKE (35555)

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