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+# Medical-Treatment-Cancer
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+A lot has been said during the past several years about how precision medicine and, more concretely, how genetic testing is going to disrupt the way diseases like cancer are treated.
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+But this is only partially happening due to the huge amount of manual work still required. Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). 
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+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 text-based clinical literature.
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+We need to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations.
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+This problem was a competition posted on Kaggle with a award of $15,000. This was launched by Memorial Sloan Kettering Cancer Center (MSKCC), accepted by NIPS 2017 Competition Track, because we need your help to take personalized medicine to its full potential.
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+You can check all details about the competition from following link : https://www.kaggle.com/c/msk-redefining-cancer-treatment