6 citations · 6 across the 9 of their papers we have counts for
10 papers · 1 filter
Cite What You Explore: Budget-Aware LLM Reasoning over Medical KGs with Verifiable Evidence
Chen Chen, Dongjie Wang, Mei Liu +1
Post-discharge risk prediction from electronic health records (EHRs) is difficult because many dependencies that link discharge-time observations to downstream complications, such…
Dual-Scale Relational Graph Transformers for Ecosystem-Aware Fraud Detection
Mohsen Nayebi Kerdabadi, Xinrou Li, Yao Xiao +2
Account takeover (ATO) fraud is a growing threat to digital banking, requiring effective detection while minimizing friction for legitimate customers. Production systems predominan…
REFINE: LLM Refinement over Budgeted Text-Attributed Graphs for Personalized Medical Concept Representation
Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Dongjie Wang +1
Learning rich medical concept representations is essential for EHR prediction. Text-attributed knowledge graphs (TKGs) provide a natural foundation by organizing heterogeneous medi…
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…
DT-BEHRT: Disease Trajectory-aware Transformer for Interpretable Patient Representation Learning
Deyi Li, Zijun Yao, Qi Xu +4
The growing adoption of electronic health record (EHR) systems has provided unprecedented opportunities for predictive modeling to guide clinical decision making. Structured EHRs c…
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…
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…
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…
Meta-Learning on Augmented Gene Expression Profiles for Enhanced Lung Cancer Detection
Arya Hadizadeh Moghaddam, Mohsen Nayebi Kerdabadi, Cuncong Zhong +1
Gene expression profiles obtained through DNA microarray have proven successful in providing critical information for cancer detection classifiers. However, the limited number of s…
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…