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cross-modal-attention

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A Multimodal Deep Learning framework for early ICU outcome prediction (Length of Stay and Mortality) on MIMIC-III. Features bi-LSTM vital-sign encoding, an MLP for clinical + lab data, 8-head Cross-Modal Attention Fusion, Platt temperature scaling calibration, and an interactive Streamlit clinical decision support dashboard.

  • Updated Jun 8, 2026
  • HTML

Multimodal emotion recognition on MELD using cross-modal Transformer fusion of BERT, Wav2Vec2, and ViT — staged fine-tuning, AMP, cached tensor preprocessing, 60.66% Weighted F1 on 7-class imbalanced data.

  • Updated Mar 2, 2026
  • Python

Official implementation of "Hierarchical Multimodal Fusion with Phased Training for Automated Pain Recognition" — ACIIW 2025. Fuses physiological signals, 4 video streams & audio via cross-modal attention and a learnable ensemble with a 3-phase training curriculum.

  • Updated Jun 22, 2026
  • Python

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