Title: Breast Cancer Prediction using different Support Vector Machine (SVM) Kernels

Biography:

Dr. Bright Keswani is working as Associate Professor at Suresh Gyan Vihar University, Jaipur. He has a long standing of teaching at graduate and postgraduate level for more than 15 years at various Institutions. He has been taught many courses in M.Tech, MCA, M.Sc., PGDCA, MBA and BCA, BBA Programs in past years. Apart from regular Teaching, Research and  Administrative work, he is associated with Software Industry and providing Consultancy on ‘Project Planning and Designing’ to the team of Software Professionals. To his credit there are a number of research articles which have appeared in leading Journals; some of which have been presented in International/National Conferences and included in Conference Proceedings, leading International/National level Magazines, and in-house Journals of corporate sector. Beside this, he is associated as Member/Senior Member/Global Member and Life Member of various National/International Societies (Technical) including ‘Computer Society of India’, CSTA.  Also, he is working as Editor-In-Chief for Suresh Gyan Vihar University-Journal of Engineering & Technology, ‘Reviewer’ for various International Journals,  such  of Computer Application in Engineering, Technology and Science (IJ-CA-ETS) and as a member of the Editorial Board of International Journal of Computer Applications in Engineering, Technology and Sciences (IJ-CA-ETS). As a prolific writer in the arena of Computer Sciences and Information Technology, he penned down a number of books on Operating System  (ISBN No: 13/978-81-8496-324-3), E-Banking and Security Transactions (ISBN No: 978-93-80311-07-4), Software Engineering (ISBN No: 81-88870-88-9) and (ISBN No: 13/978-85-8496-312-0), Elementary Computer Applications (ISBN No: 13/978-81-8496-061-7), Introduction to Computer Science (ISBN No: 13/978-81-8496-264-2) and Programming in Visual Basic. He has authored ‘Self Learning Material’ of Computer Science for Virdhaman Mahaveer Open University, Kota and Bhoj University, Madhya Pradesh, Suresh Gyan Vihar University, Jaipur etc.  Being as ‘Organizing Secretary’ and ‘Convener’ he has been organized various Conferences, Seminars and Workshops at the Department of Computer Applications, Suresh Gyan Vihar University.

Abstract

Statement of the Problem: Cancer is one of the most dangerous as well as heterogeneous disease. Breast Cancer is the most common forms of Cancer among women. Mammograms, Breast ultrasound, etc. are some of the medical test, commonly prescribed by the doctors for the diagnosis of breast cancer. But they are not always appropriate at the beginning stages of breast cancer. These routine checkups are prescribed to every woman after crossing certain age limit and thus exposed to radiation as side effects of it causes increased risk of cancer. Therefore, there is a need of an alternate solution other than costly and risky medical tests. This paper presents the use of machine learning algorithms for easy reorganization of breast cancer. A model is hereby proposed using different kernels of Support Vector Machine for the prediction of breast cancer tumor.