A Data Driven Decision Making Platform Essay - 842 Words

In this dissertation, a data-driven decision making platform is developed focusing on individuals at high risk of getting breast and ovarian cancers due to their BRCA gene mutations. First a likelihood estimation model is built based on a gradient boosting model. This model is capable of identifying individuals at high risk of having BRCA mutations based on their family and personal history of cancers. Then, a Markov decision process (MDP) model is formulated to help BRCA mutation carriers and their health providers to find effective intervention actions (based on cost or quality-adjusted life years) to prevent breast and ovarian cancers. Finally, a robust MDP (RMDP) model is presented to study the sensitivity of MDP optimal strategies under uncertainty. In what follows, I present a summary of findings in Chapters 2, 3, and 4 of this dissertation. In Chapter 2, four machine learning classifiers are used to find the likelihood of having BRCA mutation based on detailed personal and family history of cancer information. The data used for validation of the models emerges from a recent nation-wide survey study (ABOUT) of those who requested BRCA genetic testing through one of the commercial health insurance companies in the United States. This is the first study evaluating existing well-known BRCA risk estimation models using data on general population in the United States. The models considered were gradient boosting model (GBM), random forest, support vector machines, andShow MoreRelatedAccenture : Strategic Decision Making1648 Words   |  7 Pagesimpact typically will yield an invaluable prize—greater and more credible clarity around ROI. 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