52 citations · 89 across the 16 of their papers we have counts for
7 papers · 1 filter
Intersectional Fairness in Vision-Language Models for Medical Image Disease Classification
Yupeng Zhang, Adam G. Dunn, Usman Naseem +1
Medical artificial intelligence (AI) systems, particularly multimodal vision-language models (VLM), often exhibit intersectional biases where models are systematically less confide…
MRG-R1: Reinforcement Learning for Clinically Aligned Medical Report Generation
Pengyu Wang, Shuchang Ye, Usman Naseem +1
Medical report generation aims to automatically produce radiology-style reports from medical images, supporting efficient and accurate clinical decision-making.However, existing ap…
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic Approximation
Shuchang Ye, Usman Naseem, Mingyuan Meng +1
Medical language-guided segmentation, integrating textual clinical reports as auxiliary guidance to enhance image segmentation, has demonstrated significant improvements over unimo…
MRGAgents: A Multi-Agent Framework for Improved Medical Report Generation with Med-LVLMs
Pengyu Wang, Shuchang Ye, Usman Naseem +1
Medical Large Vision-Language Models (Med-LVLMs) have been widely adopted for medical report generation. Despite Med-LVLMs producing state-of-the-art performance, they exhibit a bi…
MedCFVQA: A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering
Shuchang Ye, Usman Naseem, Mingyuan Meng +2
Medical Visual Question Answering (MedVQA) is crucial for enhancing the efficiency of clinical diagnosis by providing accurate and timely responses to clinicians' inquiries regardi…
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets
Yongpei Ma, Pengyu Wang, Adam Dunn +2
Medical Visual Question Answering (MVQA) systems can interpret medical images in response to natural language queries. However, linguistic variability in question phrasing often un…
Med-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generation
Hao Wang, Shuchang Ye, Jinghao Lin +2
Automated medical report generation (MRG) is increasingly used to reduce the burden of manual reporting and for decision support. Large vision-language models (LVLMs) hold great pr…