---
license: mit
tags:
  - medical-imaging
  - computational-pathology
  - survival-analysis
  - multimodal
  - tcga
datasets:
  - TCGA
library_name: pytorch
---

# ProtoPathway

Pretrained checkpoints, preprocessed cohort data, and the curated pathway
graph for **ProtoPathway**, an interpretable-by-design multimodal framework
for cancer survival prediction.

See the [code repository](https://github.com/AmayaGS/ProtoPathway) for usage,
training, and evaluation instructions.

## Layout

```
pathways/                              shared curated Reactome + Hallmark pathways
cohorts/{cohort}/
    gene_expression.csv                preprocessed expression matrix
    bipartite_graph.pt                 cohort-specific gene-pathway graph
    labels.csv                         survival times, events, and bins
    data_splits.pkl                    5-fold CV splits (SurvPath-compatible)
    checkpoints/best_fold_{0..4}.pt    trained model weights
```

## Cohorts

Five TCGA cohorts: BRCA (N=714), BLCA (N=359), COADREAD (N=227),
HNSC (N=392), STAD (N=318). Gene expression is the preprocessed
SurvPath release. WSI patch features (UNI2-h) are not redistributed
here and should be obtained from the
[Mahmood Lab](https://huggingface.co/MahmoodLab/UNI2-h) directly.

## Quick load

```python
from huggingface_hub import snapshot_download

# Everything for one cohort plus the shared pathway file
snapshot_download(
    repo_id="AmayaGS/ProtoPathway",
    local_dir="./assets",
    allow_patterns=["cohorts/TCGA-BLCA/*", "pathways/*"],
)
```

## Citation

```bibtex
@article{protopathway2026,
  title   = {ProtoPathway: Biologically Structured Prototype-Pathway Fusion for Multimodal Cancer Survival Prediction},
  author  = {Amaya Gallagher-Syed, Costantino Pitzalis, Myles J. Lewis, Michael R. Barnes, Gregory Slabaugh},
  year    = {2026}
}
```