Precision VISSTA

Description

The overall goal of Precision VISSTA is to develop methods in the preprocessing, statistical and predictive analysis, and interactive visualization of big data from heterogeneous, time-varied mobile health and survey data. We develop exploratory visualization methods for personalized temporal trend and pattern discovery of these data for patients with inflammatory bowel disease (IBD). Our aim is to communicate and interpret computationally predicted disease outcomes, derived from applications of novel machine learning methods, to enable precise recommendations for lifestyle modifications and improve IBD outcomes.

Publications

• Periphery Plots for Contextualizing Heterogeneous Time-Based Charts

Websites

• Precision VISSTA homepage
• Periphery Plots demo

Software

GitHub

• Periphery Plots source code

Funding

• QuBBD - Statistical & Visualization Methods for PGHD to Enable Precision Medicine (NIH 1R01EB025024)
  National Institutes of Health (NIBIB) & National Science Foundation