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bioRxiv · 10.1101/2023.10.30.564783

Mining the neuroimaging literature

Dockes, J.·Oudyk, K. M.·De La Vega, A. M.·Poline, J.-B.
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Abstract

Automated analysis of the biomedical literature (literature-mining) offers a rich source of insights. However, such analysis requires collecting a large number of articles and extracting and processing their content. This task is often prohibitively difficult and time-consuming. Here, we provide tools to easily collect, process and annotate the biomedical literature. In particular, pubget is an efficient and reliable command-line tool for downloading articles in bulk from PubMed Central, extracting their contents and meta-data into convenient formats, and extracting and analyzing information such as stereotactic brain coordinates. Labelbuddy is a lightweight local application for annotating text, which facilitates the extraction of complex information or the creation of ground-truth labels to validate automated information extraction methods. Further, we describe repositories where researchers can share their analysis code and their manual annotations in a format that facilitates re-use. These resources can help streamline text-mining and meta-science projects and make text-mining of the biomedical literature more accessible, effective, and reproducible. We describe a typical workflow based on these tools and illustrate it with several example projects.

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Dockes, J., Oudyk, K. M., De La Vega, A. M., Poline, J.-B.. 2023-11-02. Mining the neuroimaging literature. https://doi.org/10.1101/2023.10.30.564783

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