Research at AMIA

With the conclusion of IEEE VIS and our multiple paper presentations in Vancouver, our attention has started shifting to the upcoming AMIA Annual Symposium in Washington, DC.  Our group (and collaborators) will be presenting two abstracts during the five day meetings.  Both abstracts are related to our PrecisionVISSTA project funded by the NIH.

In the first abstract, we present an overview of the project including a focus on the challenges of extracting actional insights from Bring-You-Own-Device mHealth data:

Arlene E. Chung, Kimberly Glass, Jacob Leisey-Bartsch, Lucas Mentch, Nils Gehlenborg, David Gotz. Precision VISSTA: Bring-Your-Own-Device (BYOD) mHealth Data for Precision Health. Abstract and Oral Presentation at AMIA Annual Symposium (2019).

The second abstract focuses more specifically on machine learning methods for prediction and inference:

Tim Coleman, Lucas Mentch, Kimberly Glass, David Gotz, Nils Gehlenborg, Arlene E. Chung. Precision VISSTA: Machine Learning Prediction and Inference for Bring-Your-Own-Device (BYOD) mHealth Data. Abstract and Oral Presentation at AMIA Annual Symposium (2019).

Look for preprints of the abstracts on the publication page where they’ll soon be posted.


Sch of Inform and Libr Science