tags:
- Survival-Analysis
[Under review] Replicating Patient Follow-Up with Hierarchical Directed Graphs for Head and Neck Cancer Survival Analysis 🧪🔬🎯
✅ Official HuggingFace repository of the paper "Replicating Patient Follow-Up with Hierarchical Directed Graphs for Head and Neck Cancer Survival Analysis".
📄 Preprint, under review for MIDL 2026: [arXiv preprint coming soon].
🧩 Method Overview
We propose H2DGSurv (Hierarchical Directed Heterogeneous Graph), a Graph Neural Network architecture for multimodal survival prediction that models the clinical pathway as a directed heterogeneous graph with temporal progression.
📂 Available resources
h2dg.pt: PyTorch model weights.
folds_5.csv: Pandas DataFrame indicating cross-validation splits for each of the 5 folds.
🚀 Source code
PyTorch model implementation is available on github: source code
🙌 Acknowledgments
We acknowledge Kist et al. 2024 for making the HANCOCK dataset available.
Useful Links
🔗 Citation
This project is based on the work by Miccinilli and Di Piazza 2025. If you use this code in your research, we would appreciate reference to the following paper:
@inproceedings{mcdp2025h2dg,
author = {Hugo Miccinilli and Theo Di Piazza},
title = {Replicating Patient Follow-Up with Hierarchical Directed Graphs for Head and Neck Cancer Survival Analysis},
booktitle = {Arxiv preprint},
year = {2025},
}