International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

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Research Paper | Biological Engineering | India | Volume 7 Issue 8, August 2018

A Comprehensive Study of Machine Learning Models in Radiogenomics

Eash Sharma | Ashwin Garg

Abstract: The ever increasing medical data has led to an increasing interest and demand for a personalized treatment setup in which each individual has its own personalized treatment plan. Specifically talking, Radiation Oncology has generated a lot of input as well as output data through which it has been able to capture the interest of the Machine Learning Methodologies. Going further, Radiogenomics, in particular, the study of genetic variation associated to radiation has been seen as a potentiate user of a lot of Machine Learning approaches. Currently, uniform doses specific to the tumor are being used. The contribution of genetics to radiations far exceeds the current understanding of risk variants. In this paper, we study the applications of Machine Learning in the Radiogenomics field which have been compared and contrasted to overcome the shortcomings of the current situation.

Keywords: Radiogenomics, Machine Learning, Personalized Treatment, Radiation Oncology

Edition: Volume 7 Issue 8, August 2018,

Pages: 10 - 13

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How to Cite this Article?

Eash Sharma, Ashwin Garg, "A Comprehensive Study of Machine Learning Models in Radiogenomics", International Journal of Science and Research (IJSR), Volume 7 Issue 8, August 2018, pp. 10-13,

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