Deep learning and segmentation: Identifying patients on their treatment journey

Join Bill Wyatt, VP of Data Science at Healthgrades, as he gives us an overview of deep learning and segmentation models as it pertains to patient identification and patient journey segmentation. During this discussion we will review Healthgrades methodology for future (potential) hospital patient identification using deep learning strategies. As an advancement of this fairly standard CRM type of process we will discuss advanced segmentation models that identify patients by clinical situation and at various parts of their journey with the goal of optimizing communication to unique clinical segment and journey stage.

I currently direct a team of data scientists and database developers analyzing over 45 million patient records and data from 240 million unique web visits per year. We provide analytic support for clinicians, hospital consultants, marketing, PR, and sales teams. My current role as VP allows me to work with multiple teams across the company to optimize analytic processes and automate standardized statistical processes. Specialties: Healthcare Data, Healthcare Analytics, Statistical analysis, consulting, programing languages (R, SQL, PHP, Matlab, SPSS, SAS), Longitudinal studies, large data sets, exploratory analysis, regression, non-parametric techniques