Diagnosis of Breast Cancer using Machine Learning Algorithms
Creators
- 1. UG Student, Department of Information Science, JSS Academy of Technical Education, Bangalore, Karnatala, India
- 2. Assistant Profesor, Department of Information Science, JSS Academy of Technical Education, Bangalore, Karnatala, India
Description
Breast cancer is one on the most well-known kind of malignant growth influencing ladies from all around the globe. If not diagnosed at an early stage it can lead to many complications or even death. This disease can affect an individual due to genes, environmental affects and many other factors. In today’s world with very advanced technologies and surgical procedures, the treatment of cancer has somewhat become easier. Machine learning and artificial intelligence techniques has played a vital role in detection, analysis and visualization of cancer cells in the human body. In this paper a review about the various machine learning algorithms used for the detection of cancerous cells have been presented. Some of the algorithms reviewed are K-nearest neighbors, random forest, and support vector machine etc., for detection of cancerous tumor.
Files
(23-29) Diagnosis of Breast Cancer.pdf
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(327.2 kB)
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Additional details
References
- Mohd Rasoul Al-headed, Abdulsalam Alarabeyyat (2017), "Breast Cancer Detection using K-nearest Neighbours Machine Learning Algorithm", IEEE, Liverpool, UK, pp. 75–85
- Farzana Kabir Ahmad, Nooraini Yusoff (2013), "Classifying Breast Cancer Types Based on Fine Needle Aspiration Biopsy Data Using Random Forest Classifier", IEEE, Bangi, Malaysia
- Meriem Amrane, Saliha Oukid, Ikram Gagaoua, Tolga Ensar (2018), "Breast Cancer Classification Using Machine Learning", IEEE, Istanbul, Turkey
- Dana Bazazeh, Raed Shubair (2016), "Comparative Study of Machine Learning Algorithms for Breast Cancer Detection and Diagnosis", IEEE, Ras Al Khaimah, United Arab Emirates
- N Marline Joys Kumari, Krishna Kishore KV, MIEEE (2018), "Prognosis of Diseases Using Machine Learning Algorithms: A Survey", IEEE, Coimbatore, India
Subjects
- Computer Science / IT Journals
- http://matjournals.com/Engineering-Journals.html