Breast cancer severity degree predication using data mining techniques in the Gaza Strip

العناوين الأخرى

توقع درجة خطورة سرطان الثدي باستخدام تقنيات تنقيب البيانات في قطاع غزة

مقدم أطروحة جامعية

Tafish, Muhammad Husni Husayn

مشرف أطروحة جامعية

al-Hulays, Ala Mustafa

الجامعة

الجامعة الإسلامية

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

تكنولوجيا المعلومات

دولة الجامعة

فلسطين (قطاع غزة)

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2017

الملخص الإنجليزي

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.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

عدد الصفحات

56

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-905704