Automatic detection and extraction of key resources from tables in biomedical papers

Our pipelines allow the detection and extraction of key resources from tables with much higher accuracy, enabling the deployment of automated research resource extraction tools on BioRxiv to help authors correct unidentifiable key resources detected in their articles and improve the reproducibility of their findings. The code, table-specific language model, annotated training and evaluation data are publicly available.

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Publication Details

Journal
BioData Mining
Published
2025-03-20
DOI
https://doi.org/10.1186/s13040-025-00438-9
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Automatic detection and extraction of key resources from tables in biomedical papers

İbrahim Burak Özyurt, Anita Bandrowski
BioData Mining
Biomedical Text Mining and Ontologies
article

Automatic detection and extraction of key resources from tables in biomedical papers

İbrahim Burak Özyurt, Anita Bandrowski
article en

Abstract

Our pipelines allow the detection and extraction of key resources from tables with much higher accuracy, enabling the deployment of automated research resource extraction tools on BioRxiv to help authors correct unidentifiable key resources detected in their articles and improve the reproducibility of their findings. The code, table-specific language model, annotated training and evaluation data are publicly available.

BioData MiningVol. 18(1)
University of California San Diego (US), Université Bourgogne Franche-Comté (FR)
Silicon Valley Community Foundation, National Institutes of Health
Decent work and economic growth
Openalex Percentile: Top 95%
Biomedical Text Mining and Ontologies
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