Predicting Breast Cancer Recurrence Using Machine Learning Techniques

2016 ◽  
Vol 49 (3) ◽  
pp. 1-40 ◽  
Author(s):  
Pedro Henriques Abreu ◽  
Miriam Seoane Santos ◽  
Miguel Henriques Abreu ◽  
Bruno Andrade ◽  
Daniel Castro Silva
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Recurrence ◽  
Breast Cancer Recurrence ◽  
Machine Learning Techniques ◽  
Learning Techniques

Survey of Breast Cancer Detection Using Machine Learning Techniques in Big Data

2019 ◽  
Vol 21 (3) ◽  
pp. 80-92
Author(s):  
Madhuri Gupta ◽  
Bharat Gupta
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Research Work ◽  
Cancer Recurrence ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Common Disease ◽  
Learning Techniques ◽  
Learning Frameworks ◽  
Processing Engine

Cancer is a disease in which cells in body grow and divide beyond the control. Breast cancer is the second most common disease after lung cancer in women. Incredible advances in health sciences and biotechnology have prompted a huge amount of gene expression and clinical data. Machine learning techniques are improving the prior detection of breast cancer from this data. The research work carried out focuses on the application of machine learning methods, data analytic techniques, tools, and frameworks in the field of breast cancer research with respect to cancer survivability, cancer recurrence, cancer prediction and detection. Some of the widely used machine learning techniques used for detection of breast cancer are support vector machine and artificial neural network. Apache Spark data processing engine is found to be compatible with most of the machine learning frameworks.

Breast Cancer Prediction Using Deep Learning and Machine Learning Techniques

2020 ◽  
Author(s):  
MONIKA TIWARI ◽  
Rashi Bharuka ◽  
Praditi Shah ◽  
Reena Lokare
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Deep Learning ◽  
Machine Learning Techniques ◽  
Cancer Prediction ◽  
Learning Techniques
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