9 citations · 9 across the 3 of their papers we have counts for
12 papers
Subtyping patients with chronic disease using longitudinal BMI patterns
Md Mozaharul Mottalib, Jessica C Jones-Smith, Bethany Sheridan +1
Obesity is a major health problem, increasing the risk of various major chronic diseases, such as diabetes, cancer, and stroke. While the role of obesity identified by cross-sectio…
AgenticSum: An Agentic Inference-Time Framework for Faithful Clinical Text Summarization
Fahmida Liza Piya, Rahmatollah Beheshti
Large language models (LLMs) offer substantial promise for automating clinical text summarization, yet maintaining factual consistency remains challenging due to the length, noise,…
NAST: Improving Negation Handling in Medical Vision-Language Models through Negation-Aware Selective Training
Ali Abbasi, Mehdi Taghipour, Rahmatollah Beheshti
Negation is a fundamental linguistic operation in clinical reporting, yet vision-language models (VLMs) frequently fail to distinguish affirmative from negated medical statements.…
A Multimodal Data Processing Pipeline for MIMIC-IV Dataset
Farzana Islam Adiba, Varsha Danduri, Fahmida Liza Piya +3
The MIMIC-IV dataset is a large, publicly available electronic health record (EHR) resource widely used for clinical machine learning research. It comprises multiple modalities, in…
Toward Revealing Nuanced Biases in Medical LLMs
Farzana Islam Adiba, Rahmatollah Beheshti
Large language models (LLMs) used in medical applications are known to be prone to exhibiting biased and unfair patterns. Prior to deploying these in clinical decision-making, it i…
Reward Hacking Mitigation using Verifiable Composite Rewards
Mirza Farhan Bin Tarek, Rahmatollah Beheshti
Reinforcement Learning from Verifiable Rewards (RLVR) has recently shown that large language models (LLMs) can develop their own reasoning without direct supervision. However, appl…