Xiongcai Cai

Healthcare systems are under increasing pressure to identify strategies to improve the current patterns of care. Although unstructured data analytics have been widely reported in big data, the importance of time series has not been fully explored yet. Real-time prediction of patient outcomes could benefit greatly from big data in health and time series analysis. In particular, prediction of patient outcome is an important indicator to assess healthcare delivery and hospital management. Rapidly identifying those patients at highest risk has a great potential to improve the quality of care, reduce avoidable harm and costs.

Social influence refers to the behavioral change of individuals affected by others in a network, whose applications include marketing, advertisement, propaganda and recommendations. This research asims at social influence analysis and its theoretical development and system implemetation ...

A novel theoretical framework for the data partitioning problem in computer vision. The framework is based on level set methods that are derived from variational calculus and involve a curve-based objective function which integrates both boundary and region based information in a generic form. The proposed approaches within the framework provide original solutions to two important problems in variational methods, namely parameter tuning and information fusion, collectively termed Learning Level Sets.