Predicate the ability of extracorporeal shock wave lithotripsy (ESWL) to treat the kidney stones by used combined classifier
Other Title(s)
توقع قدرة تقنية تفتيت الحصاة بموجات صادمة من خارج الجسم (ESWL) على علاج حصى الكلى باستخدام المصنفات المدمجة
Joint Authors
Tawfiq, Lubab Ahmad
al-Tayyar, Sukaynah Shukri Mahmud
Husayn, Samirah Shams
Source
al-Qadisiyah Journal for Computer Science and Mathematics
Issue
Vol. 11, Issue 1 (31 Mar. 2019), pp.41-52, 12 p.
Publisher
University of al-Qadisiyah College of computer Science and Information Technology
Publication Date
2019-03-31
Country of Publication
Iraq
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone.
Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment.
The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on.
Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or to using another remedy technique.
In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classifier (NCC).
The samples had been taken from 2850 actual sufferers cases that had been treated at Urology and Nephrology center of Iraq.
The results from three cases have been compared to actual treatment results of (ESWL) for trained and non-trained cases and compared the results of three models.
The results show that (NCC) approach is the most accurate method in prediction the efficient of uses (ESWL) remedy in treatment the kidney stone.
American Psychological Association (APA)
Husayn, Samirah Shams& Tawfiq, Lubab Ahmad& al-Tayyar, Sukaynah Shukri Mahmud. 2019. Predicate the ability of extracorporeal shock wave lithotripsy (ESWL) to treat the kidney stones by used combined classifier. al-Qadisiyah Journal for Computer Science and Mathematics،Vol. 11, no. 1, pp.41-52.
https://search.emarefa.net/detail/BIM-971642
Modern Language Association (MLA)
Husayn, Samirah Shams…[et al.]. Predicate the ability of extracorporeal shock wave lithotripsy (ESWL) to treat the kidney stones by used combined classifier. al-Qadisiyah Journal for Computer Science and Mathematics Vol. 11, no. 1 (2019), pp.41-52.
https://search.emarefa.net/detail/BIM-971642
American Medical Association (AMA)
Husayn, Samirah Shams& Tawfiq, Lubab Ahmad& al-Tayyar, Sukaynah Shukri Mahmud. Predicate the ability of extracorporeal shock wave lithotripsy (ESWL) to treat the kidney stones by used combined classifier. al-Qadisiyah Journal for Computer Science and Mathematics. 2019. Vol. 11, no. 1, pp.41-52.
https://search.emarefa.net/detail/BIM-971642
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 51-52
Record ID
BIM-971642