Mining impactful discoveries from the biomedical literature

This method allows the collection of a large amount of time-stamped discoveries. These can be used for LBD evaluation, alleviating the long-standing issue of inadequate evaluation. It might also pave the way for more fine-grained LBD methods, which could exploit the diversity of these past discoveries to train supervised models. Finally the dataset (or some future version of it inspired by our method) could be used as a methodological tool for systematic reviews. We provide an online exploration tool in this perspective, available at https://brainmend.adaptcentre.ie/ .

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Publication Details

Journal
BMC Bioinformatics
Published
2024-09-16
DOI
https://doi.org/10.1186/s12859-024-05881-9
Citations
2
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.47

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article

Mining impactful discoveries from the biomedical literature

Declan O’Sullivan, Orla M. Hardiman, Mark Heverin, Erwan Moreau
2 citations
BMC Bioinformatics
Biomedical Text Mining and Ontologies
0.47
article

Mining impactful discoveries from the biomedical literature

Declan O’Sullivan, Orla M. Hardiman, Mark Heverin, Erwan Moreau
article en
2 citations

Abstract

This method allows the collection of a large amount of time-stamped discoveries. These can be used for LBD evaluation, alleviating the long-standing issue of inadequate evaluation. It might also pave the way for more fine-grained LBD methods, which could exploit the diversity of these past discoveries to train supervised models. Finally the dataset (or some future version of it inspired by our method) could be used as a methodological tool for systematic reviews. We provide an online exploration tool in this perspective, available at https://brainmend.adaptcentre.ie/ .

BMC BioinformaticsVol. 25(1)
Trinity College Dublin (IE)
EU Joint Programme – Neurodegenerative Disease Research, Science Foundation Ireland
No poverty
Openalex Percentile: Top 35%
Biomedical Text Mining and Ontologies
0.47
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