Overview of the ImageCLEFmed 2021 concept & caption prediction task
O Pelka, A Ben Abacha… - Proceedings of the …, 2021 - arodes.hes-so.ch
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 …
challenges that werealready run from 2017–2020. The objective is to extract UMLS-concept …
Diagnostic captioning: a survey
Diagnostic captioning (DC) concerns the automatic generation of a diagnostic text from a set
of medical images of a patient collected during an examination. DC can assist …
of medical images of a patient collected during an examination. DC can assist …
Overview of the ImageCLEF 2018 caption prediction tasks
A García Seco de Herrera, C Eickhof… - Working Notes of …, 2018 - repository.essex.ac.uk
The caption prediction task is in 2018 in its second edition after the task was first run in the
same format in 2017. For 2018 the database was more focused on clinical images to limit …
same format in 2017. For 2018 the database was more focused on clinical images to limit …
A multilevel transfer learning technique and LSTM framework for generating medical captions for limited CT and DBT images
RV Aswiga, AP Shanthi - Journal of digital imaging, 2022 - Springer
Medical image captioning has been recently attracting the attention of the medical
community. Also, generating captions for images involving multiple organs is an even more …
community. Also, generating captions for images involving multiple organs is an even more …
Overview of the ImageCLEFmed 2020 concept prediction task: Medical image understanding
O Pelka, CM Friedrich… - Proceedings of the …, 2020 - arodes.hes-so.ch
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 …
being proposed at ImageCLEF 2017, the medical task is in its 4th edition this year, as the …
Overview of the ImageCLEFmed 2019 concept detection task
O Pelka, CM Friedrich… - Proceedings of CLEF …, 2019 - arodes.hes-so.ch
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 …
edition of the medical caption task, after it was rst proposed in ImageCLEF 2017. Concept …
Overview of ImageCLEF 2017: Information extraction from images
This paper presents an overview of the ImageCLEF 2017 evaluation campaign, an event
that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) labs …
that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) labs …
Clinical natural language processing with deep learning
The emergence and proliferation of electronic health record (EHR) systems has
incrementally resulted in large volumes of clinical free text documents available across …
incrementally resulted in large volumes of clinical free text documents available across …
[PDF][PDF] AUEB NLP Group at ImageCLEFmed Caption 2019.
We present the systems that AUEB's NLP Group used to participate in the ImageCLEFmed
2019 Caption task. The goal of this task is to automatically select medical concepts related to …
2019 Caption task. The goal of this task is to automatically select medical concepts related to …
Melinda: A multimodal dataset for biomedical experiment method classification
We introduce a new dataset, MELINDA, for Multimodal biomEdicaL experImeNt methoD
clAssification. The dataset is collected in a fully automated distant supervision manner …
clAssification. The dataset is collected in a fully automated distant supervision manner …