Precision Health with Mobile Health Data
Under construction. More information will be posted soon. In the meantime, please browse the publications listed below to learn more about the work taking place in our lab as part of this project.
Publications
Precision VISSTA: Bring-Your-Own-Device (BYOD) mHealth Data for Precision Health
A Bring-Your-Own-Device (BYOD) model for contributing mobile health (mHealth) data enables real-world data collection as patients go …
November 2019
American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract
Precision VISSTA: Machine Learning Prediction and Inference for Bring-Your-Own-Device (BYOD) mHealth Data
Precision VISSTA is a bring-your-own-device (BYOD) mobile health (mHealth) patient-powered research study focused on Inflammatory Bowel …
November 2019
American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract
Periphery Plots for Contextualizing Heterogeneous Time-Based Data
Patterns in temporal data can often be found across different scales, such as days, weeks, and months, making effective visualization …