An Application of Expert System for Diagnosing

Fever Caused by Viral Infection

Oktoria and Cheng-Hong Yang Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan

Email: oktoria.ok@gmail.com, chyang@cc.kuas.edu.tw

Li-Yeh Chuang

Department of Chemical Engineering, I-Shou University, Kaohsiung, Taiwan

Email: chuang@isu.edu.tw

Abstract—A fever, also known as a high temperature, is not

caused by an illness. It’s usually a symptom of an

underlying condition, most often an infection. In children

with fever, accompanying symptoms such as lethargy,

fussiness, poor appetite, sore throat, ear pain, vomiting and

diarrhea. Some parents think they should not go to the

hospital when children get fever, because they will be

ridiculed. As a first-aid solution, An Application of expert

system (AExS) can help parents to identify fever caused by

viral infection. It implements forward chaining as the

technique of searching through rule-base system. Some

programming code were also written in PHP for making

deduction of new fact from rules in the knowledge base. The

web based expert system enables user to diagnose the

children’s disease anytime and anywhere, just by accessing

the internet. It is very interesting and has created

considerable importance system to diagnose fever caused by

viral infection.

Index Terms—fever, symptom, expert system, forward

chaining, rule-base system, knowledge base

I. INTRODUCTION

Fever is usually associated with physical discomfort.

Many experts believe that fever is a natural bodily

defense against infection. There are also many non-

infectious causes of fever. As fevers range to 104 F (40C)

and above, however, there can be unwanted consequence,

particularly for children. These can include delirium and

convulsions. Although a fever is easy to measure,

determining its cause can be hard. Besides a physical

exam, the doctor will ask about symptoms, conditions

and medications.

The part of the brain called the hypothalamus controls

body temperature. The hypothalamus increases the

body’s temperature as a way to fight the infection.

However, many conditions other than infectious may

cause a fever. Cause of fever include bacterial infections,

viral infections, medications, illicit drugs, illness related

to heat exposure and allergies

Computer-based methods are increasingly used to

improve the quality of medical services. Artificial

Manuscript received January 1, 2016; revised June 24, 2016.

Intelligence (AI) is the area of computer science and it is

applied for decision making, diagnosis, pattern

recognition, and analysis of evidence. Furthermore, an

application of the scientific study of AI, expert systems

area able to use human knowledge through an

interference engine to solve problem that require a human

expertise [1]. This system (AExS) allows the user

(parents) to find out symptoms by providing questions

related to conditions that appeared similar to the

symptoms. Then, it diagnoses fever caused by viral

infection based on its artificial knowledge. The data

which is used by AExS came from books and a few

electronic website.

II. METHODS

Factual knowledge relevant to the problems is realized

as data or as a database or bases. The skills needed to use

the knowledge are available to solve problems, and as a

guide to acquire new facts and to learn new skills, are

realized as rules. Rule-based systems require that the

expert’s knowledge and thinking patterns should be

explicitly specified [2]. Hence, obtaining this knowledge

and writing proper rules is called the knowledge

acquisition phase. The writer is going to represent a

knowledge base of skills as a set of rules.

An expert system rule may be formulated as

if A then B (1)

where A is a set of conditions on data and B is a set of

instructions to be carried out if the rule is fired. In

forward chaining (Fig. 1), that sequence is followed.

Figure 1. Knowledge base of forward chaining

The rules are examined to see which rules are made

fireable by the data, that is, A is satisfied, and a rule or

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rules selected for firing. When the rule is fired, the set of

instructions B is executed. This is the way most rule-

based expert systems work, including AExS. Forward

chaining is reasoning from facts (symptoms) to the

conclusion (fever) resulting from those facts.

The most popular type of expert system today is the

rule-based system [3]. A rule-based system consist of IF-

THEN rules, facts, and an interpreter that control which

rules is invoked depending on the facts in working

memory. It is appropriate methodology for all medical

domains and tasks for the following reasons: cognitive

adequateness, explicit experience and subjective

knowledge, automatic acquisition of subjective

knowledge, and system integration [4]. Rule based

system presents an essential technology of building

intelligent Clinical Support System for medical diagnoses

that can aid significantly in improving the decision

making of the physicians.

Computer assisted application for patient’s diagnosis

and treatment seems to be more recent area of interest.

Diagnosis is the identification of the nature and cause of a

certain phenomenon. Diagnosis is used in many different

disciplines with variations in the use of logic, analytics,

and experience to determine “cause and effect”. The

expert diagnosis (or diagnosis by expert system) is based

on experience with the system. In addition, by using this

experience, a mapping is built that associates the

observations to the corresponding diagnoses effectively

and efficiently. The experience can be provided by

human operators who translate human knowledge into a

computer language.

Figure 2. Working of medical expert

Novaliendry [5] designed Expert System to diagnose

vitamin deficiency in humans in the form of desktop-

based application. This application uses forward chaining

method and technique of depth first search engines.

Santosh [6] introduced a Diagnosis Expert System (DExS)

with forward reasoning. DExS helps to diagnose diseases

based on user’s answers to specific questions which are

asked by the system. Computer Assisted Diagnoses for

Red Eye (CADRE) is a rule-base Expert System that

assists in red eye diagnosis and treatment. It was

introduced by Asghar [7]. CADRE evaluates the risk

factors of 20 eye diseases and works just like an

ophthalmologist.

A comprehensive study of medical expert systems for

diagnosing of various diseases was presented by Jimmy

[8]. It provides a brief overview of medical diagnostic

expert systems and presents an analysis of already

existing studies. In the Fig. 2 the simulation of medical

expert systems is presented. S1 and D1 denote the first

symptom and first disease respectively. In general Si Dj

denotes the “i” symptom of “j” disease.

The logic of AExS like this: if it has a positive answer

to the symptom, it goes on with the symptoms from that

disease. If only one symptom from the disease is negative,

it moves to the first symptom from the next disease.

III. ANALYSIS AND SYSTEM DESIGN

Distinct diagnosis tools have been used as a approach

before designing the Application of Expert System

(AExS). In [8] explained that the performance of expert

system depends on these factors: (1) The accuracy and

other parameters of expert system depend on the

knowledge base. (2) The knowledge base should have

relevant knowledge. (3) There should be stress on

knowledge acquisition, a stage in which knowledge is

gathered.

The knowledge in expert systems may be either

expertise, or knowledge that is generally available from

books, magazine, and knowledgeable persons [3]. So,

symptom information for conditions involving a fever

caused by viral infection has been gathered from various

sources [9]-[11]. It may vary on each child and only the

doctor can give sufficient diagnosis.

Rule-based experts system has been used to construct

the AExS. It is better-suited representations for

explanation as their inferences can provide transparency

because of the explicit way in which the knowledge is

represented [12]. Fig. 3 shows the most important

modules that make up a rule-based expert system.

Figure 3. Structure of AExS

An end user (parent and doctor) would communicate

with the system via a user interface and explanation

facility that would interact with an expert system

inference engine. Parents only choose symptoms which

are asked by the system, while doctors can add and edit

the disease and the rule.

One of the most popular approaches to knowledge

presentation is to use production rules, sometimes called

IF-Then rules (Table I). Some of benefits of IF-THEN

rules are that they are modular, each defining a relatively

small and, at least in principle, independent piece of

knowledge. New rules may be added and old ones deleted

usually independently of other rules.

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TABLE I. PRODUCTION RULE

Rule 1: If fever

And anorexia (eating disorder)

and headache and vomiting

and muscle pain and painful swelling of one or both parotid glands

and sore ears

Then Epidemic parotitis (Mumps)

Rule 5: If fever

and anorexia (eating disorder)

and severe headache and vomiting

and malaise (uneasiness) and cough

and nausea

and sudden high fever and low blood pressure

and bleeding gums and fingers and tip of nose feel cold

and lethargy(tiredness)

and feel agitated

and mouth cyanosis

and acting fussy / fussiness Then Dengue Fever

Rule 2:

If fever and malaise (uneasiness)

and coryza (head cold,sneezing)

and conjunctivitis (red eyes) and cough

and red flat rash (macular rash) and papular rash

Then Morbili (Measles)

Rule 5:

If fever and loss / poor appetite

and headache

and vomiting and body aches

and nausea and abdominal pain

and lethargy(tiredness)

and dark urine and fatty liver / enlargement of liver

and stools are pale or clay-colored Then Hepatitis B

Rule 3:

If fever

and anorexia (eating disorder)

and headache

and malaise (feeling tired) and cough

and aching muscles and the small red dots on the face, scalp, torso, upper

arms and legs, small bumps, blisters and pustules

Then Varicella (Chickenpox)

Rule 7:

If fever

and weakness

and swollen lymph nodes (lymphadenopathy/lymphadenitis)

and weight loss and high fever

and sweats (particularly at night) and chronic diarrhea

and opportunistic infections

Then AIDS

Rule 4:

If fever

and anorexia (eating disorder) and headache

and vomiting and muscle pain

and sore throat

and nausea and abdominal pain

and hyperemic pharyngeal

and neck stiffness and pains in the arms and legs

and having a convulsion

and suffering a neurological disorder Then Poliomyelitis

Rule 8:

If fever

and vomiting and sore throat

and feel tired and mouth sore

and sores or blisters may appear in or on the mouth and on the hands, feet, and

sometimes the buttocks and skin rash

and insomnia

and sweat out

Then Hands-foot-and-mouth disease

TABLE II. DISEASES DIAGNOSED IN AEXS

No Name of Disease

1 Epidemic parotitis (Mumps)

2 Morbili (Measles)

3 Varicella (Chickenpox)

4 Poliomyelitis

5 Dengue Fever

6 Hepatitis B

7 AIDS

8 Hands-foot-and-mouth disease

A rule based system will contain global rules and facts

about knowledge domain covered. During a particular run

of the system a database of local knowledge may also

established, relating to the particular case in hand.

The application of expert system diagnoses fever

caused by viral infection involving 8 kind of diseases

usually suffered by the children (Table II). It helps

parents to acquire the required solution regarding the

unusual disorder attack their children. The expert rules

were built up on the symptom of each kind of diseases,

and they were offered using inference tree and deduced

using forward-chaining technique.

The inference tree provides a schematic view of the

inference process (similar to a decision tree). Each rule is

composed of the symptoms and a disease. In the diagram

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19© 2016 Journal of Life Sciences and Technologies

below (Fig. 4) each of these is represented by a node.

Branches connect the symptoms and diseases.

Figure 4. The inference tree of AExS

The Inference tree will make easier to draw up the

knowledge base and rules of the diagnosis of fever caused

by viral infection. Inference engine directs the search

through the knowledge base. It dictates which rule to

“fire”. The AExS implements forward chaining as the

technique of searching through rule-base system. This

method is helpful in recognizing the symptoms which is

felt by the children, while parent is given the facility to

choose the existing symptoms.

Figure 5. ERD

The Entity Relationship(E-R) diagram shows the

entities for which information need to be stored and the

relationship between those entities. AExS consists of six

entities (Fig. 5) such as disease, rule, symptom, user,

tmp_analysis and tmp_disease.

IV. RESULT

System tests, such as logic tests, debugging, rule

checking were carried out by knowledge engineer to

ensure the system would work correctly.

In the expert system, rules are required to implement

the desired knowledge. User (doctors) can add and edit

the rule. Fig. 6 show the screen of designed rules.

Figure 6. Designed rules

Figure 7. Selection of general symptoms

Figure 8. Form dialogue consultation result

AExS provides diagnostic assistance especially

concerned with fever caused by viral infection. User

(parents) only choose symptoms which are asked by the

system. Fig. 7 shows the interface screen to accept the

input values of symptoms.

In a few minutes after choosing the symptoms, the

system will determine disease suffered by the children,

the detail information, and suggestion of treatment. The

Fig. 8 below is the view of the result of the consultation

form dialog.

On the form dialog consultation result will be

displayed along with the diagnosis and solution form

based on input data from the consultations.

V. CONCLUSION

AExS contains knowledge of fever caused by viral

infection involving 8 kind of diseases. It accommodates

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to input all kind of disease. The inference chain of this

system has strong-coupling between rules in the

knowledge base. It means “if the firing of one rule is

guaranteed to make another rule fire”. Therefore, a strong

link in the inference chain that leads from valid

symptoms to a valid conclusion (disease).

The explanation component would combine with the

inference engine to provide explanation that could follow

a consultation and provide postadvice explanation-called

feedback. Not only providing feedback, this system

should be complete with a feedforward explanation, that

provides the user with a means to find out why a

questions is being asked during a consultation (i.e.,

during the symptom input stage). Then, this system

should be complete with the experimental result to know

the system performance.

The process of constructing AExS is in many ways

similar to that of designing and building any large

computer program or a suite of programs. It is very

interesting and has created considerable importance

system to diagnose fever caused by viral infection. It was

developed with web as the basis, which will ease the user

to access the application anytime and anywhere. However

user (parents) only choose symptoms which are asked by

the system. Then the system will determine disease

suffered by the children, the detail information, and

suggestion of treatment.

ACKNOWLEDGMENT

I would like to express my gratitude to all those who

gave me the possibility to complete this paper. The

Special thank goes to DIKTI and State University of

Padang, Indonesia.

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Oktoria is a PhD student of the Department

of Electronic Engineering at National

Kaohsiung University of Applied Sciences, Taiwan since Fall 2015. He received his

Bachelor Degree (S.Pd) from State University of Semarang, Indonesia, 2005. And his Master

Degree (M.T) was received from Gadjah

Mada University, Indones ia, 2007. Since 2008 he has been being a lecturer at State

University of Padang, Indonesia. His research

interest are in genetic algorithm, expert system and bioinformatics.

Cheng-Hong Yang is a professor of the Department of Electronic Engineering at

National Kaohsiung University of Applied Sciences, Tai-wan. He received his M.S. and

Ph.D. degrees in computer engineering from

North Dakota State University in 1988 and 1992, respectively. His principal research

interest now are in evolutionary computation, bioinformatics, and assistive tool

implementation.

Li-Yeh Chuang is a professor and director of

the Department of Chemical Engineering & Institute of Biotechnology and Chemical

Engineering at I-Shou University, Kaohsiung,

Taiwan. She received her M.S. degree from the Department of Chemistry at the

University of North Carolina in 1989 and her Ph.D. degree from the Department of

Biochemistry at North Dakota State

University in 1994. Her main area of research are Bioinformatics, Biochemistry and Genetic Engineering.

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