Estimate breast cancer recurrence risk from clinical and treatment data. Built for registry analysis and research teams.
A validated model that estimates recurrence probability from surgery, age, tumour size, and treatment variables, supporting registry reporting and research.
Recurrence data is often incomplete and hard to analyse at scale. This model helps teams estimate risk and review treatment patterns from available records.
Collect surgery, age, tumour size, and chemotherapy variables
Generate recurrence risk estimates with traceable model coefficients
Review outputs through research, registry, or clinical review workflows
Validate findings with subject matter experts and local data
Risk Analytics
Predict Type II diabetes risk from clinical biomarkers. Enter patient data and get a risk score with clear review bands.
Risk Analytics
Predict osteoporosis risk from demographic and clinical data. Designed for prevention planning and research teams.
Machine Learning Solutions
Custom machine-learning models for health data: classification, forecasting, segmentation, and risk prediction.