Data Analytics for Cancer Survival and Treatment

The decreased cost and improved methods of genetic profiling offer a more thorough way of analyzing the genetic makeup of cancer and discovering genes that contributes to the variations in a patient’s clinical outcome. The explosive amount of genetic data generation creates the opportunity for big data analytics to translate huge amounts of raw genetic cancer data combined with clinical data into knowledge that can be applied to help future patients.

Integration of personal genetic information with clinical data through big data analytics offers an opportunity to revolutionize the healthcare paradigm by offering personalized treatment, predicting patient outcome, improving drug efficacy, and establishing opportunities to introduce new healthcare economic models.

In this Knowledge Sharing article, Sara He, Diego Gallo, William Schneider, and Wei Lin discuss the methodology and analysis of genetic information for a specific use case sample of patients suffering from Chronic Lymphocytic Leukemia, a slow progressing blood cancer.

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