Call for Papers

The 2012 Workshop on Visual Analytics in Healthcare will provide an opportunity for participants to discuss visual analysis applications in the healthcare domain. The focus of this year's workshop will be on Open Health Data initiatives. In addition to sharing and discussing use cases, techniques, and applications in this area, participants will be able to meet with program officers involved in major open health data initiatives and learn about funding opportunities. The workshop will allow participants to showcase their ongoing work on visualization and data mining techniques and to learn more about emerging sources of open health data.

Topics and Scope

Topics of interests include but are not limited to:

• Visual analysis and exploration of longitudinal clinical trial data
• Visual data mining of electronic health records
• Visualization of prescriptions drugs and interactions
• Improving operating room (OR) workflow with visual analytics
• Outcome forecasting or prediction
• Visual analytics for patient safety
• Pandemic forecasting and tracking
• Visual analytics in surgery / radiology / OR / emergency room (ER)
• Improving patients understanding with visual analytics
• Clinical dashboards
• Data summarization
• Visual data fusion
• Position papers advocating for specific visual analytics topics in healthcare

Paper Submission and Format Guidelines

We invite 2-4 page paper submissions that address any of the topics listed above. Shorter submissions are strongly encouraged, and papers selected for inclusion in the workshop will be given an opportunity to share their work with the workshop audience. In addition, an electronic copy of the workshop proceedings will be made available online.

Papers should be formatted in the IEEE VisWeek format style.

Important Dates

• Deadline for submission: September 5, 2012
• Notification of Acceptance: September 15, 2012
• Camera-ready Papers Due: October 1, 2012
• VAHC 2012: October 17, 2012

Organizers

Jesus J. Caban (NICoE, Naval Medical Center / jesus.caban at nih.gov)
David Gotz (IBM T. J. Watson Research Center / dgotz at us.ibm.com)