Innovation in Big Data Analytics Applications of Mathematical Programming in Medicine and Healthcare

Risk and decision models and predictive analytics have long been cornerstones for advancement of business analytics in industrial, government, and military applications. In particular, multi-source data system modeling and big data analytics and technologies play an increasingly important role in modern business enterprise. Many problems arising in these domains can be formulated into mathematical models and can be analyzed using sophisticated optimization, decision analysis, and computational techniques. In this talk, we will share some of our successes in healthcare, defense, and service sector applications through innovation in predictive and big data analytics through the modeling and computational advances in integer programming. Specifically, the first model is a discrete support vector machine predictive model that incorporates comprehensive factors related to demographics and socioeconomic status, clinical and hospital resources, operations and utilization, and patient complaints and risk factors for global prediction of readmission and treatment outcome of patients. The second model describes an outcome-driven personalized treatment planning model for cancer patients.