Leaf is a powerful, fun, lightweight web application for querying clinical data. Leaf helps query clinical databases of nearly any data model for cohort estimation and data extraction. Leaf seamlessly integrates with clinical databases and existing enterprise authentication systems to unleash the potential of translational biomedical research.
- Flexible: Clinical databases come in all shapes and sizes. Leaf can work with nearly any clinical data model, including the OMOP Common Data Model, i2b2 and SHRINE, or other proprietary or non-standard data models. Add Leaf as a sidecar to an existing data warehouse.
- User Friendly: Leaf is designed to be simple, intuitive, and fast. Searching for diagnosis or procedural codes, labs, or whatever you point Leaf to, is easy.
- Secure: Security of protected health information is critical to any healthcare organization. Leaf implements current best security practices to make clinical data both accessible and safe.
- Open: Curious how Leaf works, how you can help, or how you can use Leaf to help researchers at your CTSA? Let us know! Leaf is an open-source project by CTSAs, for CTSAs
Leaf News Updates
Thank you to Leaf Governance Committee Member, Griffin Weber, you can now play around with Leaf using an i2b2 demo dataset: http://weberdemo.hms.harvard.edu/leaf. (Select “Research” and “No” and “De-Identified” for the series of questions at the beginning to access...
New admin panel features; please visit the GitHub for documentation and steps on how to upgrade: https://github.com/uwrit/leaf/releases
Need help deploying Leaf at your CTSA? Please join us every Monday at 9a PT on zoom- bit.ly/uwleaf
Please check out Griffin Weber's lecture on "Rewriting i2b2: CQ2 and Leaf".
This map above shows the institutions that are currently piloting Leaf (that we are aware of!) This list includes: Case Western Reserve University Harvard University Johns Hopkins University * University of Chicago * University of Colorado Denver University of...
Check out the preprint of: Leaf—An open-source, model-agnostic, data-driven web application for cohort discovery and translational biomedical research.