Model inference & clinical cohort dashboard
Compare individual predictions against cohort risk distribution and explore clinical cohort statistics.
Integrative Multi-Omics + Clinical Deep Learning model for Breast Cancer Survival risk prediction
Neural network–based models that fuse clinical data with SNPs, gene expression, CNVs, and miRNA to predict breast-cancer survival.
Upload model input
Provide a ZIP (or folder) containing the SNP/RNA/MIR/CNV/CLIN modality files. The backend runs INT inference and projects the sample on the cohort PCA.
- • Supported inputs: archive/directory with modality CSV/TSV files.
- • Risk score is computed via `scripts/run_inference.py --model INT`.
- • Outputs appear in the charts once inference completes.
Clinical details
- Age
- Pending upload
- PAM50 subtype
- Pending upload
Risk distribution
Upload or select an individual to view the percentile comparison vs. the TCGA test set.