The Forefront of
UTI Prediction
UTI Prediction
in topological data analysis and
machine learning, right at your
finger tips.
Reliable
We take reliability seriously - thats why we've spent years building out the most reliable tools on the cutting edge of academia.
Collaborative
We work side by side with hopsitals to deliver the tools they need.
Complementary
We're not here to impose. We're here to complement so you can do what you do best.
Trustworthy
We give you more than just a prediction - we show our work.
Not your standard
prediction tool.
to get the most reliable predictions available.
Real-time Risk Scoring.
Predict UTI risk in seconds for patients with VUR, using clinically relevant features like reflux grade, gender, and BBD status.
Handles Missing Data.
Our model is built to work with incomplete recordsâsmart imputation strategies ensure accurate predictions even when data is missing.
Virtual Patient Modeling.
Generates virtual patient cohorts to better represent clinical diversity and improve generalizability of predictions.
Topological Learning.
Uses advanced topological representation learning to capture structure in the data and boost prediction reliability.
Year-over-Year Accuracy.
Our models consistently achieve high performance in our testing environment, maintaining strong predictive power on future data and accurately identifying evolving patient risk over time.
Clinician-Friendly Interface.
Designed for in-room decision supportâsimple, clean predictions delivered where and when they matter most.
Small, Interpretable Models.
Efficient logistic regression models mean clinicians get transparent, fast, and trustworthy results.
Built for Deployment.
Optimized for integration into EHR systems and point-of-care toolsâreal-time inference, minimal compute load, maximum impact.
Security First.
Built with robust safeguards and compliance-ready infrastructure to keep patient data protected at every layer.
Frequently asked questions:
- Who is this prediction tool for?
- The tool is designed for clinicians managing pediatric patients with vesicoureteral reflux (VUR), helping them assess UTI risk quickly and accurately.
- How does the tool handle missing data?
- Instead of dropping incomplete records, we use virtual patient sampling and topological learning to intelligently fill in gaps, maintaining prediction quality.
- Is the model explainable?
- Yes. We prioritize interpretability by using streamlined logistic regression modelsâso clinicians can understand what drives each prediction.
- Can this integrate with our existing workflow?
- Absolutely. The tool is built for real-time use and can be adapted to in-room systems or EHR platforms with minimal friction.