Implementation of Predictive Data Mining Techniques for Identifying Risk Factors of Early AVF Failure in Hemodialysis Patients
المؤلفون المشاركون
Rezapour, Mohammad
Sepehri, Mohammad Mehdi
Khavanin Zadeh, Morteza
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-06-04
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Arteriovenous fistula (AVF) is an important vascular access for hemodialysis (HD) treatment but has 20–60% rate of early failure.
Detecting association between patient's parameters and early AVF failure is important for reducing its prevalence and relevant costs.
Also predicting incidence of this complication in new patients is a beneficial controlling procedure.
Patient safety and preservation of early AVF failure is the ultimate goal.
Our research society is Hasheminejad Kidney Center (HKC) of Tehran, which is one of Iran's largest renal hospitals.
We analyzed data of 193 HD patients using supervised techniques of data mining approach.
There were 137 male (70.98%) and 56 female (29.02%) patients introduced into this study.
The average of age for all the patients was 53.87 ± 17.47 years.
Twenty eight patients had smoked and the number of diabetic patients and nondiabetics was 87 and 106, respectively.
A significant relationship was found between “diabetes mellitus,” “smoking,” and “hypertension” with early AVF failure in this study.
We have found that these mentioned risk factors have important roles in outcome of vascular surgery, versus other parameters such as “age.” Then we predicted this complication in future AVF surgeries and evaluated our designed prediction methods with accuracy rates of 61.66%–75.13%.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Rezapour, Mohammad& Khavanin Zadeh, Morteza& Sepehri, Mohammad Mehdi. 2013. Implementation of Predictive Data Mining Techniques for Identifying Risk Factors of Early AVF Failure in Hemodialysis Patients. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-501589
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Rezapour, Mohammad…[et al.]. Implementation of Predictive Data Mining Techniques for Identifying Risk Factors of Early AVF Failure in Hemodialysis Patients. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-501589
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Rezapour, Mohammad& Khavanin Zadeh, Morteza& Sepehri, Mohammad Mehdi. Implementation of Predictive Data Mining Techniques for Identifying Risk Factors of Early AVF Failure in Hemodialysis Patients. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-501589
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-501589
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر