activity
20242026
collaborators

6 papers

cs.LG2026

Text-Attributed Knowledge Graph Enrichment with Large Language Models for Medical Concept Representation

Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Chen Chen +2

In electronic health record (EHR) mining, learning high-quality representations of medical concepts (e.g., standardized diagnosis, medication, and procedure codes) is fundamental f…

cs.CL2026

RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

Arya Hadizadeh Moghaddam, Drew Ross, Mohsen Nayebi Kerdabadi +2

Large Language Models (LLMs) have shown strong promise for mining Electronic Health Records (EHRs) by reasoning over longitudinal clinical information to capture context-rich patie…

cs.LG2026

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…

cs.LG2025

Spatio-Temporal Directed Graph Learning for Account Takeover Fraud Detection

Mohsen Nayebi Kerdabadi, William Andrew Byron, Xin Sun +1

Account Takeover (ATO) fraud poses a significant challenge in consumer banking, requiring high recall under strict latency while minimizing friction for legitimate users. Productio…

cs.LG2024

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…

cs.LG2024

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…