About

Big data is changing our world and the way scientific breakthroughs are discovered. As healthcare organizations continue to collect most of their information in digital form, the resulting massive collections are creating many data challenges from (a) clinicians trying to analyze large amounts of unstructured, multi-modal, and longitudinal data to effectively diagnose and monitor the progression of a particular disease; to (b) patients who are confronted with the difficult task of understanding the correlations between clinical values and their own patient-generated health data; to (c) healthcare organizations who are faced with the problem of understanding the nature of disease in broad populations, and improving overall operational performance while still maintaining the quality of patient care and safety.

Visualization and visual analytics techniques have the potential to assist in many of the informatics data challenges by providing intuitive and interactive interfaces to explore, analyze, and compare large collection of structured and structured clinical data. However, to be successful, visualization-based systems must be developed to align with the unique demands of the healthcare system.
This tutorial will introduce the concepts of visual analytics in healthcare by

  • Teaching some of the core concepts of data visualization
  • Introducing the basic concepts of visual analytics
  • Demonstrating case studies of how visual analytics can be used to analyze healthcare data
  • Providing step-by-step explanations of how to start creating advanced visualization systems and dashboards with commercial and open-source applications. The tutorial will mix instructional material with hands-on exercises.

Speakers

David Gotz University of North Carolina, Chapel Hill
Jesus J Caban Walter Reed National Military Medical Center
Adam Perer IBM T.J. Watson Research Center
Joshi NYU

Join the community:

(1) Join our mailing list:

Email address:
(optional) Your name:
Only emails that are approved by the moderators are distributed to the mailing list. Spam-free mailing list.


(2) Follow us on Twitter:

@VisAnalyticsHC


(3) Join AMIA Working Group on Visual Analytics in Healthcare

AMIA VIS-WG