activity
20232026
most citedQuestion-Answering System Extracts Information on Injection Drug Use from Clinical Notes

3 citations · 5 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

A Multi-Stage Validation Framework for Trustworthy Large-scale Clinical Information Extraction using Large Language Models

Maria Mahbub, Gregory M. Dams, Josh Arnold +9

Large language models (LLMs) show promise for extracting clinically meaningful information from unstructured health records, yet their translation into real-world settings is const…

cs.CL2026

Visual Word Sense Disambiguation with CLIP through Dual-Channel Text Prompting and Image Augmentations

Shamik Bhattacharya, Daniel Perkins, Yaren Dogan +3

Ambiguity poses persistent challenges in natural language understanding for large language models (LLMs). To better understand how lexical ambiguity can be resolved through the vis…

cs.AI2025

HARNESS: Human-Agent Risk Navigation and Event Safety System for Proactive Hazard Forecasting in High-Risk DOE Environments

Ran Elgedawy, Sanjay Das, Ethan Seefried +7

Operational safety at mission-critical work sites is a top priority given the complex and hazardous nature of daily tasks. This paper presents the Human-Agent Risk Navigation and E…

cs.AI2024

Advancing NLP Security by Leveraging LLMs as Adversarial Engines

Sudarshan Srinivasan, Maria Mahbub, Amir Sadovnik

This position paper proposes a novel approach to advancing NLP security by leveraging Large Language Models (LLMs) as engines for generating diverse adversarial attacks. Building u…

cs.CL2024★ 1 cited

Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approach

Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan +4

Substance use disorder (SUD) poses a major concern due to its detrimental effects on health and society. SUD identification and treatment depend on a variety of factors such as sev…

cs.IR2024★ 1 cited

Dynamic Q&A of Clinical Documents with Large Language Models

Ran Elgedawy, Ioana Danciu, Maria Mahbub +1

Electronic health records (EHRs) house crucial patient data in clinical notes. As these notes grow in volume and complexity, manual extraction becomes challenging. This work introd…

cs.AI2023★ 3 cited

Question-Answering System Extracts Information on Injection Drug Use from Clinical Notes

Maria Mahbub, Ian Goethert, Ioana Danciu +9

Background: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can be…