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Check out the documentation for more information.
Multimodal Prostate Cancer Survival Model (MRI + Clinical)
This repository contains outputs from the main multimodal survival model, which integrates both imaging and structured clinical variables.
The model combines:
- T2-weighted MRI
- ADC MRI
- HBV MRI
- Structured clinical variables
MRI features are extracted using a 3D ResNet-18 encoder, while clinical features are processed via a multilayer perceptron (MLP).
The fused representation is optimized with a Cox proportional hazards survival loss.
Contents
main_model_outputs.zipmodels/— best checkpoints for all 5 foldspredictions_fold*.csv— per-fold survival predictions
Training Settings
- 5-fold cross-validation
- Epochs: 30
- Batch size: 2
- Learning rate: 3e-5
- Weight decay: 1e-5
- Pad size: 40
- MRI encoder frozen: Yes
- Loss: Cox proportional hazards
- Optimizer: Adam
Performance
- Mean C-index: 0.8152 ± 0.1189
Notes
This model achieved the highest overall performance across all tested configurations.
It serves as the primary model in the accompanying technical report, demonstrating the benefit of integrating MRI with clinical variables.
For complete training code and documentation, visit:
https://github.com/AliEngineering/multimodal-prostate-survival