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Breast cancer severity predication using deep learning techniques
Joint Authors
al-Halis, Ala Mustafa Darwish
Tafish, Muhammad Husni Husayn
Source
Jordanian Journal of Computetrs and Information Technology
Issue
Vol. 6, Issue 1 (31 Mar. 2020), pp.94-102, 9 p.
Publisher
Princess Sumaya University for Technology
Publication Date
2020-03-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
Breast cancer is one of the most common types of cancer most often affecting women.
It is a leading cause of cancer death in less developed countries.
Thus, it is important to characterize the severity of the disease as soon as possible.
In this paper, we applied deep learning methods to determine the severity degree of patients with breast cancer, using real data.
The aim of this research is to characterize the severity of the disorder in a shorter time compared to the traditional methods.
Deep learning methods are used because of their ability to detect target class more accurately than other machine learning methods, especially in the healthcare domain.
In our research, several experiments were conducted using three different deep learning methods, which are: Deep Neural Network (DNN), Recurrent Neural Network (RNN) and Deep Boltzmann Machine (DBM).
Then, we compared the performance of these methods with that of the traditional neural network method.
We found that the f-measure of using the neural network was 74.52% compared to DNN which was 88.46 %, RNN which was 96.79% and DBM which was 97.28%.
American Psychological Association (APA)
al-Halis, Ala Mustafa Darwish& Tafish, Muhammad Husni Husayn. 2020. Breast cancer severity predication using deep learning techniques. Jordanian Journal of Computetrs and Information Technology،Vol. 6, no. 1, pp.94-102.
https://search.emarefa.net/detail/BIM-1416459
Modern Language Association (MLA)
al-Halis, Ala Mustafa Darwish& Tafish, Muhammad Husni Husayn. Breast cancer severity predication using deep learning techniques. Jordanian Journal of Computetrs and Information Technology Vol. 6, no. 1 (Mar. 2020), pp.94-102.
https://search.emarefa.net/detail/BIM-1416459
American Medical Association (AMA)
al-Halis, Ala Mustafa Darwish& Tafish, Muhammad Husni Husayn. Breast cancer severity predication using deep learning techniques. Jordanian Journal of Computetrs and Information Technology. 2020. Vol. 6, no. 1, pp.94-102.
https://search.emarefa.net/detail/BIM-1416459
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 101-102
Record ID
BIM-1416459