Prediction of Chronic Kidney Disease Using Data Mining Techniques

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

Recently renal failure disease has spread widely all over the world, especially in Sudan, as indicated by the WHO reports. Therefore, it was necessary to use all available scientific methods to contribute in studying the factors that lead to the disease and predict it in its early stage, to decrease its widespread. In this research,data mining techniques were used to study and determine the factors that lead to Chronic Kidney Disease in its early stages, and to build models to predict the disease using the selected features. Data used in this research was collected from medical Center for Renal Failure Treatment in India. WEKA machine learning software was used in this research for all data mining operations like data exploration, feature selection, and model development. Supervised machine learning algorithms, such as Naïve Bayes, Random Forest, C4.5 Tree and Neural Networks, were used to select the important features and develop the models. Several models were built using several algorithms, each of which gave high accuracy and acceptable interpretation to the physicians. The research motivates other researchers to start working intensively in this field by forming research groups from data scientists and physicians to solve such problems using real patients’ data.

روابط وملفات

التعريف والنوع

رقم الوثيقة

099f24ea-3961-4f68-9043-4220a46a3b0a

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

2187972_1.pdf

بيانات النشر

ترجمة العنوان

توقع مرض الفشل باستخدام تقنيات التنقيب في البيانات

ألقاب المؤلفين

[{"name_ar":"تلات محي الدين وهبي","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"رانيا كراملا احمد كراملا","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

English

المصدر والدورية

اسم المصدر

Prediction of Chronic Kidney Disease Using Data Mining Techniques

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

Computer Science and Information Technology Information Technology Chronic Kidney Disease Data Mining Techniques

إشراف وإعداد

الإشراف

تلات محي الدين وهبي

الإعداد

رانيا كراملا احمد كراملا

الاقتباسات الببليوغرافية