Automatic Question Answering (QA) has been successfully applied in various domains such
as search engines and chatbots. Biomedical QA (BQA), as an emerging QA task, enables …

Abstract Medical Visual Question Answering (VQA) is a combination of medical artificial
intelligence and popular VQA challenges. Given a medical image and a clinically relevant …

In this paper, we focus on the problem of Medical Visual Question Answering (MedVQA),
which is crucial in efficiently interpreting medical images with vital clinic-relevant information …

The field of meta-learning, or learning-to-learn, has seen a dramatic rise in interest in recent
years. Contrary to conventional approaches to AI where tasks are solved from scratch using …

Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In
contrast, development in biomedical domain lags far behind due to data scarcity. To address …

Medical vision-and-language pre-training provides a feasible solution to extract effective
vision-and-language representations from medical images and texts. However, few studies …

Medical visual question answering (Med-VQA) has tremendous potential in healthcare.
However, the development of this technology is hindered by the lacking of publicly-available …

Recently a number of studies demonstrated impressive performance on diverse vision-
language multi-modal tasks such as image captioning and visual question answering by …

Images in the medical domain are fundamentally different from the general domain images.
Consequently, it is infeasible to directly employ general domain Visual Question Answering …

Medical vision-and-language pre-training (Med-VLP) has received considerable attention
owing to its applicability to extracting generic vision-and-language representations from …