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Solving Wide Predictive Modeling Problems With Clinical and Genomic Data

Kelci Miclaus, PhD, JMP Advanced Analytics R&D Manager, SAS

Precision medicine, a disease treatment and/or prevention approach that incorporates a person’s clinical and biological data, has become an integral aspect of improving medicine and the health care system. The emerging data collected by researchers and pharmaceutical companies typically has many more (thousands or even millions) variables than rows. The JMP life sciences software solutions, JMP Genomics and JMP Clinical, include several predictive modeling approaches with a comprehensive set of predictor filtering tools targeted specifically for the wide data prediction problem. We will highlight how custom-scripted analysis reports in JMP can be executed in a cross-validated predictive modeling review journal to explore the prediction space of wide life science data problems to drive better medical decisions. A new set of modeling tools for clinical subgroup analysis will also be described.

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