Author

Joydeep Chandra

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Conference Open access Sep 2026

MedFiTRG: Jointly Learning Dynamic Temporal and Cross-Patient Graphs for Clinical Outcome Prediction

Integrating heterogeneous clinical modalities, structured electronic health records (EHRs), clinical text, and medical imaging is crucial for reliable clinical prediction, yet real-world data are often sparse and imbalanced. Furthermore, prior approaches treat temporal dynamics and inter-patient relationships in isolat...

Shivani Gupta, H. Kumar, Joydeep Chandra · Proceedings of the Thirty-Fi... · 0 citations

#graph neural networks Aug 2026

Taking lessons from history: Memory Augmented Self Distillation for graph neural networks

This study introduces a novel memory-augmented self-learning framework that extracts and provides diverse learning sources for adaptive knowledge distillation from the student model itself, resulting in a 2.5-6% increase in accuracy across various benchmark datasets compared to current GNN training and self-distillatio...

Saurabh Sharma, Souvik Chowdhury, Joydeep Chandra · Data mining and knowledge di... · 0 citations