Breast Cancer Recurrence Analytics
Estimate breast cancer recurrence risk from clinical and treatment data. Built for registry analysis and research teams.
What this solution does
A peer-reviewed 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.
Outputs are model estimates for analytics and research review, not a clinical diagnosis or treatment recommendation. We document the inputs, assumptions, and limits behind every score.
Model basis: Khan, O., Ajadi, J. O., Almsned, F., Almohanna, H., Alrasheed, A., Sanusi, R. A., & Adegoke, N. A. (2025). Prognostic model for predicting recurrence in breast cancer patients in Saudi Arabia. Scientific Reports, 15(1), 18388.
Who it serves and where it applies
- Cancer registries and breast cancer research teams
- Academic collaborators working on recurrence modelling
- Oncology analytics teams
- Institutional research teams handling treatment and outcome data
- Retrospective recurrence risk estimation
- Registry-aligned breast cancer analytics
- Research prototyping for recurrence prediction models
- Treatment outcome reporting and cohort review