Personalised_Medicine

Personalized-Medicine-Redefining-Cancer-Treatment is a problem of classifying the given genetic mutations based on the literature available in the medical domain into one of the given 9 classes. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). Currently, this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from textbased clinical literature. In this project we develop a machine learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations.