Author
Duy-Cat Can
University of Engineering and Technology, VNUH
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NeuroVietCH at MEDIQA-CORE-Task-1 2026: LLM-Guided Multimodal Distillation for Brain Tumor Subtype Classification
Explainable Graph-theoretical Machine Learning: with Application to Alzheimer's Disease Prediction
The results suggest the promise of graph-theoretical machine learning for biomarker discovery, disease prediction, and understanding the neural mechanisms underlying AD.
Imputation-free transformer learning enables robust Alzheimer’s disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts
NITROGEN is proposed, an imputation-free transformer that jointly models within-patient feature dependencies and between-patient relational structure through masked and intersample attention, enabling robust multimodal learning directly from partially observed records, and shows robust probability calibration and uncer...