Diagnosing heart diseases using ontology and SWRL rules
Other Title(s)
تشخيص أمراض القلب باستخدام الأنتولوجيا و قواعد SWRL
Dissertant
al-Agha, Husam Muhammad Mustafa
Thesis advisor
University
Islamic University
Faculty
Faculty of Information Technology
Department
Information Technology
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2017
English Abstract
Heart disease is the most common disease worldwide which is considered the main cause of death.
According to cardiologists in Palestine, the heart disease was the main cause of death among the Palestinians, at a rate of 27.5% of all deaths.
The differential diagnosis between different types of heart diseases requires the results of several clinical tests.
The patient's symptoms alone are not sufficient to give an accurate diagnosis because many types of heart diseases have the same symptoms.
Currently there is no specific system in the domain of heart diseases in Palestine.
Also, available medical systems do not employ semantic approaches, they are just using database-oriented methodologies.
They are not flexible and adaptable to complex requirements and processes and lack intelligence.
This work aims to improve the diagnosis of heart diseases by exploiting Semantic Web technologies.
We use ontology and Semantic Web Rule Language (SWRL) to diagnose heart diseases.
We have built a domain ontology (HeartOnt) that covers domain knowledge of heart diseases.
The ontology contains terms, relationship and properties to be used in the approach of diagnosing heart diseases.
SWRL rules are created from valid relationships between ontology concepts to detect heart disease and estimate the risk of heart disease.
The rules are used to infer new knowledge from the ontology, knowledge base and patient data.
The proposed system was tested using a sample set of patients with heart diseases provided by a domain expert.
Results have shown that the system have correctly diagnosed 27 out of the 30 patients (ratio of correctness is 90%).
Main Subjects
Information Technology and Computer Science
No. of Pages
98
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : State of the art.
Chapter Three : Heart diseases ontology.
Chapter Four : Writing SWRL rules.
Chapter Five : The DHDOnto system.
Chapter Six : Experimental result and evaluation.
Chapter Seven : Conclusion and future work.
References.
American Psychological Association (APA)
al-Agha, Husam Muhammad Mustafa. (2017). Diagnosing heart diseases using ontology and SWRL rules. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-905426
Modern Language Association (MLA)
al-Agha, Husam Muhammad Mustafa. Diagnosing heart diseases using ontology and SWRL rules. (Master's theses Theses and Dissertations Master). Islamic University. (2017).
https://search.emarefa.net/detail/BIM-905426
American Medical Association (AMA)
al-Agha, Husam Muhammad Mustafa. (2017). Diagnosing heart diseases using ontology and SWRL rules. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-905426
Language
English
Data Type
Arab Theses
Record ID
BIM-905426
