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International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014) An Expert System Framework forInfertility in Women using Web-Based Application
Norhidayah Sukar
Nor Liyana Mohd Shuib
Department of Information Science, Department of Information System, Faculty of Computer Science and Information Faculty of Computer Science and Information Technology, University of Malaya, Technology, University of Malaya, 50603, Lembah Pantai, Kuala Lumpur, Malaysia 50603, Lembah Pantai, Kuala Lumpur, Malaysia Abstract
Emerging of technologies in the internet and fields of expert systems has offered better approaches for imparting and conveying information. Conversely, there has been a general absence of research in the area of web-based expert systems particularly in a medical diagnosis for infertility. This paper proposed an expert system framework for woman infertility diagnosis using web based application. The proposed framework intended to enhance the existing tools used to identify and diagnose infertility problems. The conceptual and technical design in conventional expert system were reviewed and the framework of knowledge engineering for developing them was redefined and analyzed. The linear model methodology is used to ensure the system design meets its goals. This model emphasize on knowledge acquisition process which enables the effective way in gathering precise information from expert to promote intelligent interviews. A procedure of expert system framework development is discussed. This framework can be used as guideline to develop a web-based expert system for infertility diagnosis to assist physicians with their daily practices and women who had infertility problems.
Keywords: Expert system, infertility, web based application, diagnosis.
1.
Detailed diagnostic plays a vital role in the ability of the overall system to correctly determine the symptoms and the result of possible solutions. It is important for infertility couple to refer to a specialist, such as a Reproductive Endocrinologist or urologist, or in some cases Obstetrician / Gynecologist for a complete fertility work-up and diagnosis. There are several tests and diagnostic procedures for women including pelvic ultrasound, hormone level test, basal body temperature, hysterosalpingogram (HSG), Antral follicle count, Clomiphene citrate challenge tests and others. Evaluation of infertility symptoms is the beginning stage for medical treatment of infertility as it may indicate specific causes and appropriate treatment modalities. In spite of the fact that physical examination provides important information, specific diagnostic tests are required to evaluate infertility because the factor that may contribute to infertility can be multifactorial. Infertility is defined as the inability to conceive after 1 year of unprotected intercourse. This definition is based couples, infertility results from a combination of subtle defects in fertility contributed by each partner (Falcone T). Most married couples eager to start a family don't imagine that they will have difficulty conceiving. Infertility is a critical issue for a married couple that increase anxiety and exert stress (ASRM). There is a lot information on infertility through the internet but it is impossible to solve complex problem by read through information to obtain solutions. Another alternative is by seeing specialist which can be quite expensive and time-consuming. On top of that, there are limitations on expertise acquisition from human when comparing to an expert system. International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014) This paper is being undertaken to establish a web-based infertility expert system that is capable to diagnose symptoms that can causes and contribute to infertility and provide possible solution to justify the diagnosis with logical reasons. Infertility expert system has limitation to identify the exact type of symptoms and results because some symptoms requires medical treatments or laboratory test to be confirmed. The system will diagnose by focusing on more general view of infertility related symptoms and also possible solutions. Thus, the system will emphasis on the most common infertility problems. The symptoms of infertility for women that would be diagnose through the system including the reproductive aging, infectious diseases, behavioral factors, genetic influences, Varicocele, damage to fallopian tubes, hormonal, cervical, and uterine causes. Generally, this infertility expert system will be divided into two major modules. The first module is diagnose module which acquires information about certain symptoms of infertility that are significant in diagnosing problem during consultation with the user. The second module is result or prescription module. This module presents the diagnose result to the user and present brief prescription of the diagnosed infertility symptom and causes. Thus, the expected outcomes of the system using the proposed expert system framework were to retrieve the systems given by the user and match them with the symptoms in the knowledge base. Infertility and Expert System Related Studies
Infertility Problem
Over the years, infertility problem is commonly considered as women problem.
However, it is proven and recognized that men likely to stem from the infertility problem. Recent study has shown that about one over six couples having difficulty in achieving conception at some stage during their reproductive years. For some, they believe that infertility problem will be overcome after a variable period of trying. Meanwhile, there is a case happens pregnancy ensues through the help of medical intervention. Infertility is a critical issue for a married couple that increase anxiety and exert stress. This leads to isolation from friends, family and also experiences intense feelings, such as pain, anger and fear. In recent decades, steady progress has been made in the treatment of Consequently, the expectation of being success to have a children should be in a large portion of infertile couple realistic imagination, although it may take time and many treatments attempts for this to happen. The best tools with knowledge and information appropriate in the circumstances for infertile couple to tackle their problem and successfully obtain the best solutions for themselves. Infertile couple especially female partner need to start know about their bodies and how conception takes place. They need to be concern about available treatment modalities, drawback and their efficacy. An infertility expert system like this may fulfils these objectives. In addition, this type of system ensures that the non-medical member, busy physician practitioners and especially infertility women have access to a simple yet comprehensive system that will enable them to perform optimally with their respective roles with infertility problems. Expert System
Today computers not only store, manipulate, and retrieve data; they are increasingly taking on the role of making decisions. Integrating Artificial Intelligence concepts in computer International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014) programs makes the human life easier. One of the major contribution of Artificial Intelligence has made our quest of knowledge is expert system. Expert system technology is to analyze experts' reasoning under a certain circumstance and implement this knowledge to the computer in a form of rules, data base, etc. Monitoring and diagnostics have proven to be successful application areas of expert systems (Milne, 1987). Generally, expert system is a computer program that perform a task that would otherwise perform by a human expert. This includes decision-making ability of a human expert system instead of contains the knowledge of human experts. Why build an expert system? Expert system was developed to replace human experts. Furthermore, human expert is retiring or leaving, an expert system can automate a routine task requiring a human expert and instead of replace them, expert system also aimed to assist human expert. The combination of a theoretical understanding of the problem and collection of heuristic problem-solving rules that experience has shown to be effective in the domain. Expert system are constructed by obtaining this knowledge from human expert and encoded it into a form that a computer may apply to similar problems. Web Based Infertility Expert System
The development of Infertility Expert System (IES) is based on the expert system
technique. IES is a web-based application that runs online and enables the users, specifically physician and women to early identify and diagnose related symptoms that may contribute to infertility. The system architecture of the IES comprises the major components of an expert system. The components consist of user interface, inference engine, explanation mechanism, working memory, and diagnostic knowledge base. The knowledge acquisition that were coming from the expert in the fields of infertility which includes Reproductive Endocrinologist or urologist, or in some cases Obstetrician / Gynecologist that have expertise and knowledge about infertility problem and its treatments. The target user are public user, the expert assistant, knowledge engineer, and the person who are interested in infertility problem. The public user meant here are those people who are not expert in the infertility and facing infertility problem particularly in women. The contradictory pictures on the purpose of using web-based Infertility Expert System is because of several factors. These factors include inherently portable of internet-based applications, the readily accessible of the internet, common multimedia interface provided by web-browsers and several internet-compatible tools that are available for Knowledge Based System. Meanwhile, Athappilly stated that "the use of emerging Internet technology made the development of multifunctional Artificial Intelligence systems relatively easy and less expensive, but that many users in the business arena were unaware of these technologies and their potential benefits". Thus, these technologies are making business more efficient, effective and competitive. Infertility Expert System Design
System Architecture
Infertility Expert System is a web based application which can be access in a public at
any time and any place with the only condition – internet connection is available. Web server and dynamic web pages is required to make the system web enabled. Hence, three-tier
International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014)
architecture is implemented through this system. Figure 3.1 shows the three-tier web
application architecture.
Figure 3.1: Three-tier Web Application Architecture
Below here are the brief descriptions of the three-tier architecture that applied on this
infertility expert system (IES):
User interacts with IES through the web browser (Internet Explorer, Mozilla
Firefox, Google Chrome, and Netscape Navigator) which contains a form of HTML
(ii) PHP scripting language is embedded in the HTML page.
(iii) User inputs all information required into the questions form in the web page. The
process collecting data resides in the client tier.
(iv) User's web browser sends requests for data from the previous client tier. (v) The web server (Apache) recognizes that the requested file in a PHP script, then
server interprets he file using its PHP plug-n, before responding to the page request.
(vi) The request is evaluated and passed to the data tier. (vii) A particular PHP commands connect to the MySQL database and request content
to the PHP script.
(viii) The MySQL database responds by sending the requested content to the PHP script.
(ix) The MySQL database responds by sending the requested content to the PHP script. (x) The PHP script stores the content into one or more PHP variables, and then output
the content as part of the web page.
(xi) The PHP plug-in finished up by handing a copy of the HTML it has created to the
(xii) The Web server sends the HTML to the web browser as it would a plain HTML file,
except that instead of coming directly from an HTML file, the page is the output
provided by the PHP plug-in.
Functionality Design
The development of IES will be divided into two major modules. The two major modules
are diagnose module and prescription module. Each of the modules performs different tasks.
For diagnose module which is also the main module of the IES will perform the diagnosis task by prompt questions and then provide diagnose result to the user. This diagnose module is then
International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014)
divided into two sub modules, which are Sign and Symptoms Sub Module and Result Sub
The sign and symptoms sub module requires user to answer several question for the
system to present a diagnose result. The order of the questions in the system are based on its
importance and priority. Simple questions are formed to ease the user in answering the questions and not to be hesitated or confused. Meanwhile, the result sub module is presented
when the system found a conclusion based on the answer given. The second module which is the prescription module, presented brief prescription and recommendation of possible
solutions or treatments towards the infertility problem.
Proposed Expert System Framework for Infertility
Material and Method
The Expert System was applied and used as the medical diagnosis for infertility in
women and human expert problem solving. The process for designing and development of the expert system is known as knowledge engineering. The knowledge engineering process
comprises several steps which include knowledge acquisition, architecture of the infertility expert system, and knowledge base design.
Knowledge acquisition was defined as the technique or format of acquiring, gaining,
organizing and studying knowledge and information. The authors had to review the standard guidelines for the diagnosis of infertility problem as the first step before creating the system.
Knowledge acquisition enables knowledge engineers to collect knowledge which will be stored in the knowledge base of an expert system.
The methodology to be used to ensure the system design meets its goals is called linear
model. This model emphasize on knowledge acquisition process which enables the effective way in gathering precise information from expert or specialist to promote intelligent interviews.
Knowledge source identification and selection is performed to select the knowledge sources
based on importance and availability. In this expert system, the author choose to gather sources through human expert by interviewing, and some reading materials and internet surfing.
Proposed Framework
The architecture of the infertility expert system is presented systematically through the
proposed framework as shown in Figure 4.1 below.
International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014)
Figure 4.1: The Infertility Expert System Framework
The concept of expert system in the proposed framework were constructed by obtaining
the knowledge from a human expert and coding it into a form that a computer may apply to
similar problems. Each of the component on the Figure 4.1 play an important roles for the infertility expert system. The component consists of user interface, explanation mechanism,
inference engine, knowledge base, working memory and database.
Firstly, the main of the user interface component in the proposed framework is to enable
the public user to input the potential symptom that may related to the infertility problems. On
top of that the user interface must displays the optimal decision choice for the beneficial of the user. The former is by implements an interactive display with effectiveness and efficiency in
terms of accomplishing the goal; to facilitate the task completely at hand without drawing unnecessary attention to itself. The functionality of the user interface must be design to require
a good understanding of the user. Requirement gathering in term prompt the user from the general symptoms to a specific ones to attain an accurate and best solution or results.
The inference engine plays an important part in the expert system where its models the
human process in the reasoning. It is the processor of the expert system that matches the facts
contained in the working memory with the domain knowledge in the knowledge base, to derive new information for the explanation mechanism. After that, it searches the rules for a match
between their premises and information in the working memory. When the inference engine finds a match, it adds the rules conclusion to the working memory and will continuously scan
the rules to look up for new matches. Thus, it will be used for deducing answers or results from the knowledge base.
Explanation mechanism is potentially very useful in the expert system. This is because it
can be viewed as an optional feature for infertility expert system without interfering with the functions and operation of the underlying system. The explanation mechanism provides better
understanding to the question and allows the users to restart the consultation session. The adaptation of the explanation mechanism to the user is by delivering the appropriate level of
abstraction. In addition, Clancey (1983) has reported that "the default explanation types in rule-
based expert systems are inadequate and should be enhanced with other explanatory content".
International Journal of Information Systems and Engineering (online), Volume 2, Issue 1 (April 2014)
The element in the proposed expert system that maintain the expert's domain
knowledge is called knowledge base. This models the human expert's long term memory. The
domain knowledge will be extracted from the expert and the coded into the knowledge base. Its represents the facts and rules. These rules will be applied by the inference engine to the specific
facts to deduce new conclusion. The use of rules in the knowledge base are to enable explanation capabilities and also explicitly represent knowledge.
Working memory in the expert system stimulates the short term memory of the human
expert. Equivalent to the human expert's short term memory, it contains the case facts or the facts discovered during the consultation between the expert and the advice. It also contains the
information about the infertility problem that was inferred by the system, by the matches between the knowledge in the knowledge base and the case facts obtained from the user.
In the proposed framework, the working memory and knowledge base is stored in a
table of a database using MySQL database. Each user will have a unique table of working
memory once the infertility diagnosis is started. The table of working memory will be removed from the database if and only the user exits the system.
Conclusion
In the present work, an expert system framework for infertility has been proposed and
various treatment options for infertility can be recognized through it possible symptoms. The goal of the infertility expert system is to identify the causes of infertility in women reproductive
age and to investigate the possible solutions and treatment of infertility. It is hoped that the infertility expert system is able to educate and help to solve infertility problem with particular
treatments and suggestions.
This paper has shown that there is much potential for the use of expert system
framework for solving infertility problem. The limitation of this infertility system that this
system relies merely on sign and symptoms of the information given by the user. This enable
users to check to diagnose their own infertility problem without referring to any human experts. Anyhow, for more precise results, lab test should be perform.
In summary, the essence of an expert system is to mimic expertise and distribute expert
knowledge to non-experts. Since the rapid development of the internet can enhance the usage and benefits bring out of an expert system, develop a web-based expert system is very useful in
all fields. In view of the fact that web-based expert system is so useful; more research should be carried out to develop web-based expert systems in all other fields.
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