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Cancer AI Prototype
OmicsFusionNet + sDCFE

Empowering Early Cancer Detection with Multi-Omics AI

Prototype demo for partners: RNA-seq + DNA methylation + proteomics → sDCFE → prediction. We currently prototype 10 cancer types and are actively working on 23.
Try the workflow (demo)

Upload a CSV (demo only) → the system simulates analysis and presents a mock prediction + dashboard output.

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* Demo only. This prototype simulates the pipeline for meetings and does not process user data.

Technology
  • OmicsFusionNet: multi-layer data fusion from RNA-seq, DNA methylation, and proteomics.
  • sDCFE: Synergistic Differential Cluster Feature Extraction for interpretable biomarkers.
  • Performance: validated on 3,000+ samples; early vs late-stage accuracy 94–96%.
  • Outcome: 85+ biomarkers discovered; explainable and clinically interpretable.
  • Scope: Prototype supports 10 cancer types; full program targets 23 types.
Adoption in Labs
  1. Export omics data as standard CSV matrices.
  2. Upload to Cancer AI or integrate via API.
  3. sDCFE identifies cross-omics biomarker clusters; OmicsFusionNet predicts type & stage.
  4. Review dashboard → biomarkers, confidence, interpretability overlays.
  5. Iterate with validation cohorts; move to CLIA/CE-ready workflows.
EU-ready Ideal for IHI / Horizon Europe health pilots