Breast cancer severity degree predication using data mining techniques in the Gaza Strip
Other Title(s)
توقع درجة خطورة سرطان الثدي باستخدام تقنيات تنقيب البيانات في قطاع غزة
Dissertant
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
Data mining has become a fundamental methodology for computing applications in the domain area of medicine.
Data mining is defined as the procedure that finds the valuable data from raw information sets by investigating and compressing them by considering alternate points of view.
Medical data mining is a set of methods that extract valuable and novel information from human services database to help doctors to get best diagnosis.
In this area cancer disease growth and diabetes are the top mortal disease in Gaza strip the last years.
So, data mining can be the most part utilized as these include extravagant and drawn out tests.
Extending research papers related to the discovery of breast cancer, we proposed a model to help in resolving the difficulty of determineing the degree of risk for the disease and to get best practices, abatement time and expense with the objective of advancing well-being, based on data collected from hospitals in the Gaza Strip.
The model is applying the classification technique such as SVM, ANN and KNN on the collected breast cancer data.
Which in turn predicts the severity of breast cancer.
We also, applied association rules to see what the top attributes related to high severity breast cancer are.
After evaluation and testing using SVM, KNN and ANN classifier on the breast cancer dataset, we obtain an accuracy of 78%, which is accepted rate of prediction for severity of breast cancer.
In addition, we list the most related attributes to high severity of breast cancer.
Main Subjects
Information Technology and Computer Science
No. of Pages
56
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Background theory.
Chapter Three : Literature review.
Chapter Four : Proposed intelligent model.
Chapter Five : Experimentation results.
Chapter Six : Conclusion and future work.
References.
American Psychological Association (APA)
Tafish, Muhammad Husni Husayn. (2017). Breast cancer severity degree predication using data mining techniques in the Gaza Strip. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-905704
Modern Language Association (MLA)
Tafish, Muhammad Husni Husayn. Breast cancer severity degree predication using data mining techniques in the Gaza Strip. (Master's theses Theses and Dissertations Master). Islamic University. (2017).
https://search.emarefa.net/detail/BIM-905704
American Medical Association (AMA)
Tafish, Muhammad Husni Husayn. (2017). Breast cancer severity degree predication using data mining techniques in the Gaza Strip. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-905704
Language
English
Data Type
Arab Theses
Record ID
BIM-905704
