학술논문

Breast cancer relapse prognosis by classic and modern structures of machine learning algorithms
Document Type
Conference
Source
2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Fuzzy and Intelligent Systems (CFIS), 2018 6th Iranian Joint Congress on. :120-122 Feb, 2018
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Breast cancer
Support vector machines
Biological neural networks
Prognostics and health management
Machine learning algorithms
Breast Cancer
Recurrence
Classifiers
Language
Abstract
According to medical reports, cancers are big problems in the world society. In this paper we are supposed to predict breast cancer recurrence by multi-layer perceptron with two different outputs, a deep neural network as a feature extraction and multi-layer perceptron as a classifier, rough neural network with two different outputs, and finally, support vector machine. Then, we compare the results achieved by each method. It can be understood that rough neural network with two outputs leads to the highest accuracy and the lowest variance among other structures.