Choosing Optimal Therapy by Means of Machine Learning

Student: Lukutina Anna

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 8

Year of Graduation: 2016

Nowadays, a lot of data science approaches exist for finding personalized treatment, and they are still emerging. In this work we analyze data based on treatment of children acute lymphoblastic leukaemia (ALL) by protocol MB-ALL, carried out by D.Rogachev Federal Scientific Clinical Center, Moscow and Charite Clinic, Berlin. To design a method for generating an Individualized Treatment Rule (ITR) based on previous experience given by clinical data we use Outcome Weighted Learning [1]. This method uses a kernel function as a parameter, so we analyze four kernel functions: linear, polynomial, exponetial and Gaussian. The results are presented in tables and graphs.

Full text (added May 30, 2016)

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