Big Data Analytics for Healthcare
Abstract:
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.
