Medical VQA

Medical Visual Question Answering (Med-VQA) aims to develop AI systems that can answer questions about medical images, assisting clinicians in diagnosis and decision-making. Current research focuses on improving model robustness and reliability through techniques like contrastive learning, adversarial training, and advanced attention mechanisms within large vision-language models (LVLMs). However, studies highlight significant limitations in current models' ability to handle nuanced medical questions, particularly those requiring fine-grained diagnostic reasoning, underscoring the need for more rigorous evaluation and improved model architectures. The ultimate goal is to create reliable and accurate Med-VQA systems that can enhance medical practice and improve patient care.