Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

Over the past decades, medical image analytics was greatly facilitated by the explosion of
digital imaging techniques, where huge amounts of medical images were produced with …

The classification of medical images is an essential task in computer-aided diagnosis,
medical image retrieval and mining. Although deep learning has shown proven advantages …

The availability of medical imaging data from clinical archives, research literature, and
clinical manuals, coupled with recent advances in computer vision offer the opportunity for …

This work introduces a new multimodal image dataset, with the aim of detecting the interplay
between visual elements and semantic relations present in radiology images. The objective …

Medical images are valuable for clinical diagnosis and decision making. Image modality is
an important primary step, as it is capable of aiding clinicians to access required medical …

Non-textual components such as charts, diagrams and tables provide key information in
many scientific documents, but the lack of large labeled datasets has impeded the …

This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of
the Conference and Labs of the Evaluation Forum–CLEF Labs 2022. ImageCLEF is an …

Résumé We investigated two strategies for improving Information Retrieval thanks to
incoming and outgoing citations. We first started from settings that worked last year and …

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 …