About VAHC 2018 (9th workshop on Visual Analytics in Healthcare)

The 2018 Workshop on Visual Analytics in Healthcare (VAHC 2018) is the ninth annual workshop that provides an opportunity for participants to discuss state-of-the-art data visualization techniques and review how such techniques can be applied to healthcare data.

The primary objective of the annual workshop is to bring together medical experts, leading scientists, and visionaries to discuss how visual analytics can be applied to healthcare data and discuss the areas of healthcare that need more attention from the visual analytics community.

The workshop will enable participants to showcase their ongoing work on visual analytics of healthcare-related data through podium, poster, or demo presentations, as well as to learn more about emerging techniques, software applications, and datasets.

During the last eight years the Workshop on Visual Analytics in Healthcare (VAHC) has been organized and hosted annually, alternating between the IEEE VIS conference and the AMIA Annual Symposium.

This year the VAHC 2018 workshop is affiliated with the AMIA Annual Symposium in San Francisco, California and will take place on Saturday, November 3.

For information about all previous VAHC events and to access the open-access proceedings from each of the previous workshops, please see past events.

***NEW THIS YEAR*** We will be holding a design challenge, with on-site judging by a panel of informatics professionals and visualization experts. Opportunity will be made for interested groups to sign up online and to present a sketch/wireframe of their intended visualization.

Themes for the design challenge will be based around the targeted end-user, including patients (e.g., patient-generated data, patient behavior and experience, patient education); clinicians (e.g., clinical workflows, longitudinal health records, medication visualizations, patient safety); and researchers (e.g., population health, outcome forecasting, pandemic tracking, data mining, multi-omics). Several example datasets will be suggested, though if desired, participants are welcome to use their own datasets.