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Medical Visual Question Answering

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Showing 51–97 of 97 papers

TitleStatusHype
Prompting Medical Large Vision-Language Models to Diagnose Pathologies by Visual Question Answering—0
A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering—0
A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis—0
A dataset of clinically generated visual questions and answers about radiology images—0
Alignment, Mining and Fusion: Representation Alignment with Hard Negative Mining and Selective Knowledge Fusion for Medical Visual Question Answering—0
Barriers in Integrating Medical Visual Question Answering into Radiology Workflows: A Scoping Review and Clinicians' Insights—0
BESTMVQA: A Benchmark Evaluation System for Medical Visual Question Answering—0
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets—0
CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making—0
Detecting and Evaluating Medical Hallucinations in Large Vision Language Models—0
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels—0
Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models—0
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
Enhancing Generalization in Medical Visual Question Answering Tasks via Gradient-Guided Model Perturbation—0
Free Form Medical Visual Question Answering in Radiology—0
Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering—0
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis—0
GEMeX-ThinkVG: Towards Thinking with Visual Grounding in Medical VQA via Reinforcement Learning—0
Grounded Knowledge-Enhanced Medical VLP for Chest X-Ray—0
Hierarchical Modeling for Medical Visual Question Answering with Cross-Attention Fusion—0
Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learning—0
Leveraging Medical Visual Question Answering with Supporting Facts—0
LLaVA-Ultra: Large Chinese Language and Vision Assistant for Ultrasound—0
Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model—0
Medical Visual Question Answering: A Survey—0
Medical visual question answering using joint self-supervised learning—0
MedOrch: Medical Diagnosis with Tool-Augmented Reasoning Agents for Flexible Extensibility—0
MedThink: Explaining Medical Visual Question Answering via Multimodal Decision-Making Rationale—0
MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering—0
MuVAM: A Multi-View Attention-based Model for Medical Visual Question Answering—0
OVQA: A Clinically Generated Visual Question Answering Dataset—0
Prompt-based Personalized Federated Learning for Medical Visual Question Answering—0
Q2ATransformer: Improving Medical VQA via an Answer Querying Decoder—0
RepsNet: Combining Vision with Language for Automated Medical Reports—0
R-LLaVA: Improving Med-VQA Understanding through Visual Region of Interest—0
SMMILE: An Expert-Driven Benchmark for Multimodal Medical In-Context Learning—0
Structure Causal Models and LLMs Integration in Medical Visual Question Answering—0
TM-PATHVQA:90000+ Textless Multilingual Questions for Medical Visual Question Answering—0
Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models—0
Tri-VQA: Triangular Reasoning Medical Visual Question Answering for Multi-Attribute Analysis—0
UIT-Saviors at MEDVQA-GI 2023: Improving Multimodal Learning with Image Enhancement for Gastrointestinal Visual Question Answering—0
UnICLAM:Contrastive Representation Learning with Adversarial Masking for Unified and Interpretable Medical Vision Question Answering—0
Vision-Amplified Semantic Entropy for Hallucination Detection in Medical Visual Question Answering—0
Visual Question Answering in the Medical Domain—0
V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL—0
WangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models—0
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering—0
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