Big Data Analytics for Healthcare



Large amounts of heterogeneous medical data have become available in various healthcare organizations (payers, providers, pharmaceuticals). Those data could be an enabling resource for deriving insights for improving care delivery and reducing waste. The enormity and complexity of these datasets present great challenges in analyses and subsequent applications to a practical clinical environment. In this tutorial, we introduce the characteristics and related mining challenges on dealing with big medical data. Many of those insights come from medical informatics community, which is highly related to data mining but focuses on biomedical specifics. We survey various related papers from data mining venues as well as medical informatics venues to share with the audiences key problems and trends in healthcare analytics research, with different applications ranging from clinical text mining, predictive modeling, patient similarity, genetic data analysis, privacy on medical data  and medical images.


Tutorial Presented at the ACM SIGKDD 2013 Conference.

Part I    Part II    Part III


Tutorial Presented at SIAM International Conference on Data Mining 2013 Conference.

Presentation Slides