POD-Vis (Probing Outcomes Data with Visual Analytics) is a user-friendly web-based platform, developed at the University of Maryland Baltimore for visualizing and analyzing outcomes data. POD-Vis includes the following main features:  

1. Upload any type of clinical dataset 

2. Supports cross-sectional and longitudinal data. 

3. Easily visualize, analyze, and explore your data to generate and test hypotheses 

4. Create diverse study subgroups with ease based on any variable (e.g. sex, age, symptom severity, labs, imaging, treatment)  

5. Data queries based on the simple structure of predictors and outcomes 

6. Create predictor-based or outcomes-based analyses with ease 

7. Visualize individual patient data in the context of predefined cohorts 

8. Precision-medicine: Use ML models to predict outcomes for individual patients in the context of comparable cohorts.  

9. Export any table, figure, or graph for use in grants, manuscripts, and powerpoints. 

10. Share one or more harmonized datasets with robust access controls.  

11. Export labeled cohorts in Machine Learning (ML)-ready format for training models or importing into other statistical software packages.

Getting Started