The 2022 ImageCLEFmedical caption prediction and concept detection tasks follow similar
challenges that were already run from 2017–2021. The objective is to extract Unified …

Résumé The 2021 ImageCLEF concept detection and caption prediction task follows similar
challenges that werealready run from 2017–2020. The objective is to extract UMLS-concept …

This paper presents the systems that were implemented for the participation of AUEB's NLP
Group in the sub-tasks of the 2021 ImageCLEFmed Caption task, which included a Concept …

Résumé This paper describes the ImageCLEF 2019 Concept Detection Task. This is the 3rd
edition of the medical caption task, after it was rst proposed in ImageCLEF 2017. Concept …

Automated medical image analysis systems often require large amounts of training data with
high quality labels, which are difficult and time consuming to generate. This paper …

Résumé This paper describes the ImageCLEFmed 2020 Concept Detection Task. After _rst
being proposed at ImageCLEF 2017, the medical task is in its 4th edition this year, as the …

This paper presents the participation of the Image Semantics group (ImageSem) of the
Institute of Medical Information at the ImageCLEF 2018 caption task. We participated in both …

We present the methods AUEB's NLP Group used to participate in the annual
ImageCLEFmedical Caption Task. The task comprises of the Concept Detection and the …

Résumé This paper presents an overview of the ImageCLEF 2017 caption tasks on the
analysis of images from the biomedical literature. Two subtasks were proposed to the …

This article describes the methods that the AUEB NLP Group experimented with during its
participation in the 7th edition of the ImageCLEFmedical Caption sub-tasks, namely Concept …