The Rise of Mathematical Oncology
Kiran George1, R. Malathi1, J. Krishnan1
, and Nisha Susan Thomas2
1.Department of Electronics and Instrumentation Engineering, Bioengineering Group, Annamalai University, Annamalai nagar-608 002, Tamil Nadu, India
2.Department of Biochemistry and Biotechnology, Cancer Biology Group, Annamalai University, Annamalai nagar-608 002, Tamil Nadu, India
2.Department of Biochemistry and Biotechnology, Cancer Biology Group, Annamalai University, Annamalai nagar-608 002, Tamil Nadu, India
Abstract—Cancer research has produced tremendous basic and clinic levels of information. So far, to validate this information has become a most challenging task for researcher and clinician. However the information validated by mathematical models provides an opportunity for the researcher and clinician. The field of mathematical oncology has received great attention and increased enormously in the ongoing battle against cancer. This short review comprises the complexity of mathematical oncology and the new strategy of hybrid mathematical model of tumor growth. In addition we suggest how these new directions could contribute to addressing the current challenges of understanding of tumor mechanisms.
Index Terms—complexity of mathematical oncology, multiscale modeling, modeling techniques, drug modeling.
Cite: Kiran George, R. Malathi, J. Krishnan, and Nisha Susan Thomas, "The Rise of Mathematical Oncology," Journal of Medical and Bioengineering, Vol. 4, No. 4, pp. 293-296, August 2015. Doi: 10.12720/jomb.4.4.293-296
Index Terms—complexity of mathematical oncology, multiscale modeling, modeling techniques, drug modeling.
Cite: Kiran George, R. Malathi, J. Krishnan, and Nisha Susan Thomas, "The Rise of Mathematical Oncology," Journal of Medical and Bioengineering, Vol. 4, No. 4, pp. 293-296, August 2015. Doi: 10.12720/jomb.4.4.293-296