42 citations · 52 across the 13 of their papers we have counts for
5 papers · 1 filter
Physics-Informed Neural Koopman Machine for Interpretable Longitudinal Personalized Alzheimer's Disease Forecasting
Georgi Hrusanov, Duy-Thanh Vu, Duy-Cat Can +6
Early forecasting of individual cognitive decline in Alzheimer's disease (AD) is central to disease evaluation and management. Despite advances, it is as of yet challenging for exi…
MUDI: A Multimodal Biomedical Dataset for Understanding Pharmacodynamic Drug-Drug Interactions
Tung-Lam Ngo, Ba-Hoang Tran, Duy-Cat Can +3
Understanding the interaction between different drugs (drug-drug interaction or DDI) is critical for ensuring patient safety and optimizing therapeutic outcomes. Existing DDI datas…
REMEMBER: Retrieval-based Explainable Multimodal Evidence-guided Modeling for Brain Evaluation and Reasoning in Zero- and Few-shot Neurodegenerative Diagnosis
Duy-Cat Can, Quang-Huy Tang, Huong Ha +2
Timely and accurate diagnosis of neurodegenerative disorders, such as Alzheimer's disease, is central to disease management. Existing deep learning models require large-scale annot…
Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction
Narmina Baghirova, Duy-Thanh Vũ, Duy-Cat Can +6
Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of cases. AD is associated with disru…
VisTA: Vision-Text Alignment Model with Contrastive Learning using Multimodal Data for Evidence-Driven, Reliable, and Explainable Alzheimer's Disease Diagnosis
Duy-Cat Can, Linh D. Dang, Quang-Huy Tang +5
Objective: Assessing Alzheimer's disease (AD) using high-dimensional radiology images is clinically important but challenging. Although Artificial Intelligence (AI) has advanced AD…