STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications.

ABSTRACT:

Background and methods

Systematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain steps in systematic reviews, such as data extraction, are labour-intensive, which hampers their feasibility, especially with the rapidly expanding body of biomedical literature. To bridge this gap, we aimed to develop a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n = 45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n = 31 publications; multiple sclerosis, n = 244 publications).

R

SUBMITTER: Zurrer WE 

PROVIDER: S-EPMC11594395 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature