Quantifying Cross-Modal Interactions in Multimodal Glioma Survival Prediction via InterSHAP: Evidence for Additive Signal Integration

1. 1Adapt InterSHAP from classification to Cox proportional hazards models
2. 2Apply InterSHAP to quantify cross-modal interactions in glioma survival prediction
3. 3Use TCGA-GBM and TCGA-LGG data to validate the approach
4. 4Analyze results to understand the nature of cross-modal interactions

Data scientists and AI engineers on a healthcare team can benefit from this research to improve multimodal cancer prognosis models, and product managers can apply these insights to develop more effective medical diagnosis tools

💡 InterSHAP provides evidence for additive signal integration in multimodal glioma survival prediction

🧬 InterSHAP helps quantify cross-modal interactions in glioma survival prediction #AIinHealthcare