Improve model card metadata and links (#1)

- Improve model card metadata and links (f598a6d4347f30760c4437b8bd22a610045f537a)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,71 +1,70 @@
----
-license: mit
-tags:
-  - medical-imaging
-  - computational-pathology
-  - survival-analysis
-  - multimodal
-  - tcga
-  - interpretable
-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/pathways_base_*.pkl           curated Reactome + Hallmark pathway graph
-raw_inputs/                            raw files for re-running preprocessing from scratch
-    Reactome/                          Reactome hierarchy files (GMT, relations, names)
-    Hallmark/                          MSigDB Hallmark gene sets
-    {cohort}/                          rna_clean.csv, clinical CSV, SurvPath splits
-cohorts/{cohort}/                      preprocessed cohort data and trained models
-    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},
-  journal = {arXiv preprint arXiv:2605.21454},
-  year    = {2026},
-}
-```
+---
+datasets:
+- TCGA
+library_name: pytorch
+license: mit
+pipeline_tag: other
+tags:
+- medical-imaging
+- computational-pathology
+- survival-analysis
+- multimodal
+- tcga
+- interpretable
+---
+
+# ProtoPathway
+
+Pretrained checkpoints, preprocessed cohort data, and the curated pathway graph for **ProtoPathway**, an interpretable-by-design multimodal framework for cancer survival prediction.
+
+- **Paper:** [ProtoPathway: Biologically Structured Prototype-Pathway Fusion for Multimodal Cancer Survival Prediction](https://huggingface.co/papers/2605.21454)
+- **Code:** [https://github.com/AmayaGS/ProtoPathway](https://github.com/AmayaGS/ProtoPathway)
+
+## Layout
+
+```
+pathways/pathways_base_*.pkl           curated Reactome + Hallmark pathway graph
+raw_inputs/                            raw files for re-running preprocessing from scratch
+    Reactome/                          Reactome hierarchy files (GMT, relations, names)
+    Hallmark/                          MSigDB Hallmark gene sets
+    {cohort}/                          rna_clean.csv, clinical CSV, SurvPath splits
+cohorts/{cohort}/                      preprocessed cohort data and trained models
+    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},
+  journal = {arXiv preprint arXiv:2605.21454},
+  year    = {2026},
+}
+```