Abstract: Artificial Intelligence has become a core technology underlying many modern applications, especially in healthcare, where the techniques provide powerful methods for analyzing large data sets, such as medical images, electronic health records, and operational data. With the potential to speed up the diagnostic process, enable higher quality assessment of multiple conditions, and standardize reproducible decisions, providers, payers, and healthcare companies are looking to leverage these emerging technologies and close capability gaps. In this session, we examine data strategy and technical use cases involving time-series, text, and image data, and discuss the development and deployment of these solutions within Fortune 500 companies.
Bio: Michael Segala is the CEO and co-founder of SFL Scientific, a data science consulting firm that specializes in big data solutions. His firm leverages advanced machine learning and analytics techniques to provide insight into numerous industry-spanning problems, from healthcare to stock market prediction. Before founding SFL Scientific, Michael worked as a data scientist in several well-known tech companies, such as Compete Inc. and Akamai Technologies. He holds a PhD in Particle Physics from Brown University.