Text Summarization is the process of creating a summary of a certain document that
contains the most important information of the original one, the purpose of it is to get a …

Healthcare data are inherently multimodal. Almost all data generated and acquired during a
patient's life can be hypothesized to contain information relevant to providing optimal …

One of the primary challenges facing medical visual question answering (Med-VQA) is the
lack of large-scale well-annotated datasets for training. To overcome this challenge, this …

Medical visual question answering (Med-VQA) aims to accurately answer a clinical question
presented with a medical image. Despite its enormous potential in healthcare industry and …

Medical visual question answering (Med-VQA) aims to accurately answer a clinical question
presented with a medical image. Despite its enormous potential in healthcare services, the …

Understanding the relationship between figures and text is key to scientific document
understanding. Medical figures in particular are quite complex, often consisting of several …

Résumé This paper presents an overview of the inaugural edition of the ImageCLEF 2018
Medical Domain Visual Question Answering (VQA-Med) task. Inspired by the recent success …

This paper presents an overview of the ImageCLEF 2019 lab, organized as part of the
Conference and Labs of the Evaluation Forum-CLEF Labs 2019. ImageCLEF is an ongoing …

Abstract Visual Question Answering in Medical domain (VQA-Med) plays an important role
in providing medical assistance to the end-users. These users are expected to raise either a …

Abstract The Lifelog Search Challenge (LSC) is an international content retrieval
competition that evaluates search for personal lifelog data. At the LSC, content-based …