3 citations · 9 across the 6 of their papers we have counts for
7 papers
GEMeX-RMCoT: An Enhanced Med-VQA Dataset for Region-Aware Multimodal Chain-of-Thought Reasoning
Bo Liu, Xiangyu Zhao, Along He +3
Medical visual question answering aims to support clinical decision-making by enabling models to answer natural language questions based on medical images. While recent advances in…
RankLLM: A Python Package for Reranking with LLMs
Sahel Sharifymoghaddam, Ronak Pradeep, Andre Slavescu +7
The adoption of large language models (LLMs) as rerankers in multi-stage retrieval systems has gained significant traction in academia and industry. These models refine a candidate…
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis
Bo Liu, Ke Zou, Liming Zhan +7
Medical Visual Question Answering (Med-VQA) combines computer vision and natural language processing to automatically answer clinical inquiries about medical images. However, curre…
MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM
Nan Zhou, Ke Zou, Kai Ren +7
The Medical Segment Anything Model (MedSAM) has shown remarkable performance in medical image segmentation, drawing significant attention in the field. However, its sensitivity to…
Uncertainty-aware Medical Diagnostic Phrase Identification and Grounding
Ke Zou, Yang Bai, Bo Liu +9
Medical phrase grounding is crucial for identifying relevant regions in medical images based on phrase queries, facilitating accurate image analysis and diagnosis. However, current…
Uncertainty-informed Mutual Learning for Joint Medical Image Classification and Segmentation
Kai Ren, Ke Zou, Xianjie Liu +5
Classification and segmentation are crucial in medical image analysis as they enable accurate diagnosis and disease monitoring. However, current methods often prioritize the mutual…
Towards Reliable Medical Image Segmentation by Modeling Evidential Calibrated Uncertainty
Ke Zou, Yidi Chen, Ling Huang +6
Medical image segmentation is critical for disease diagnosis and treatment assessment. However, concerns regarding the reliability of segmentation regions persist among clinicians,…