CLEF eHealth Acknowledgement, Citation, and Licensing Policy
Thank you for choosing to use data, software, or other resources provided to you by the CLEF eHealth initiative. All our datasets are freely available for research purpose. The following table gives the list of datasets, the related tasks, and link to get access.
Please find below our guidelines for acknowledging and citing the initiative and its resources, together with instructions about our licensing policy.
If you use data, software, or other resources provided to you by the CLEF eHealth initiative for academic presentation, research paper, or other publication purposes, please include the following acknowledgement:
We gratefully acknowledge the contribution of the people and organizations involved in the CLEF eHealth initiative as participants, organizers, or funders.
Please cite the most relevant lab or task overview(s). The list of these overviews is available at References.
Please pay careful attention to the licensing agreement associated with each data, software, or other resource release by the CLEF eHealth initiative. You can find the details in the task specific overviews at References.
|Information extraction||2013-2014||IE from clinical reports: MIMIC II dataset has been used for two tasks in 2013, and one task in 2014.||Link|
The goal of the task is to perform named entity recognition in a corpus of biomedical articles in French.
(Link to be added)
|Information management||2014||The goal of the task is to design visualization systems for eHealth data. The corpus contains clinical reports, annotations, patient search queries, and matching relevant web documents.||Link|
|2015-2016||The goal of the 2015 task is to design correction systems for speech recognition output from nurses handovers. For the 2016 task, it is to fill out a handover form with 35 headings with information extracted from the free-form text handover reports.||Link|
|Technology assisted reviews||2017-2019||The goal of the task is to design visualization systems for eHealth data. The corpus contains clinical reports, annotations, patient search queries, and matching relevant web documents.||Link|
|Information retrieval||2013-2018||The goal of the task is to improve information retrieval systems, to better handle health consumer queries. The dataset contains queries in multiple languages, web documents, and relevance judgement (including judgements of other dimensions of relevance).||2013 document collection(also used in 2014-15)
2016-2017 document collection: Clueweb12-B13
2018 document collection: (link to be added)
2013-18 queries, qrels, etc
Link to the original page