6 citations · 6 across the 6 of their papers we have counts for
7 papers
Import What You Need: Learning When and How to Augment EHR Graphs with External Knowledge
Chen Chen, Mohsen Nayebi Kerdabadi, Dongjie Wang +2
Longitudinal prediction from electronic health records (EHRs) is limited by the sparsity and irregularity in patient trajectories, and knowledge augmentation with external knowledg…
User-Adaptive Meta-Learning for Cold-Start Medication Recommendation with Uncertainty Filtering
Arya Hadizadeh Moghaddam, Mohsen Nayebi Kerdabadi, Dongjie Wang +2
Large-scale Electronic Health Record (EHR) databases have become indispensable in supporting clinical decision-making through data-driven treatment recommendations. However, existi…
YuFeng-XGuard: A Reasoning-Centric, Interpretable, and Flexible Guardrail Model for Large Language Models
Junyu Lin, Meizhen Liu, Xiufeng Huang +12
As large language models (LLMs) are increasingly deployed in real-world applications, safety guardrails are required to go beyond coarse-grained filtering and support fine-grained,…
DeepJ: Graph Convolutional Transformers with Differentiable Pooling for Patient Trajectory Modeling
Deyi Li, Zijun Yao, Muxuan Liang +1
In recent years, graph learning has gained significant interest for modeling complex interactions among medical events in structured Electronic Health Record (EHR) data. However, e…
Compound AI Systems Optimization: A Survey of Methods, Challenges, and Future Directions
Yu-Ang Lee, Guan-Ting Yi, Mei-Yi Liu +3
Recent advancements in large language models (LLMs) and AI systems have led to a paradigm shift in the design and optimization of complex AI workflows. By integrating multiple comp…
SurvAttack: Black-Box Attack On Survival Models through Ontology-Informed EHR Perturbation
Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Bin Liu +2
Survival analysis (SA) models have been widely studied in mining electronic health records (EHRs), particularly in forecasting the risk of critical conditions for prioritizing high…
Contrastive Learning on Medical Intents for Sequential Prescription Recommendation
Arya Hadizadeh Moghaddam, Mohsen Nayebi Kerdabadi, Mei Liu +1
Recent advancements in sequential modeling applied to Electronic Health Records (EHR) have greatly influenced prescription recommender systems. While the recent literature on drug…