Secure, explainable cancer classificationyou can actually trust.
OncoSecure AI combines deep learning with Grad-CAM explainability and privacy-first design to support triage decisions across brain, breast, and lung cancer imaging.
Predicted class
Glioma
Three specialized modules
Focused on the cancers that matter most
Each module is tuned for a specific imaging modality and classification schema, so you get results grounded in the right clinical context.
Brain Tumor
MRI
Breast Cancer
Histopathology / Ultrasound
Lung Cancer
CT
Platform features
Engineered for clarity and trust
Fast inference
Upload a scan and get a predicted class with confidence scores in seconds.
Explainable outputs
Every prediction comes with a Grad-CAM heatmap showing the regions that drove the decision.
Privacy-first
Scans are processed in memory with no PHI retention or long-term image storage.
Strict validation
Uploads are validated both client-side and server-side against type and size policies.
Analytics dashboard
Track analyses across categories and confidence ranges in a single clean view.
Modular architecture
Swap the mock inference for a real model endpoint without touching the UI layer.
Explainability you can see
Grad-CAM heatmaps overlay attention regions directly on the uploaded scan, so you can verify that the model is focusing on clinically plausible structures — not artifacts or noise.
- Per-class probability breakdown
- Human-readable interpretation
- Visual attention overlay
Privacy by design
Uploads are validated, processed transiently, and never persisted beyond the scope of a single inference request. No patient identifiers, no EMR linkage, no silent retention.
- MIME + magic-byte validation
- In-memory processing only
- No third-party image uploads
Ready to explore explainable medical AI?
Try the analyze flow with your own sample scans, or explore the dashboard to see how OncoSecure AI surfaces insights across cancer categories.