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Updated: May 24, 2026
07:50
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
OpenExtract: Automated Data Extraction for Systematic Reviews in Health
Jim Achterberg1, Bram van Dijk1, Jing Meng2
1Leiden University Medical Center, The Netherlands.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
This study introduces OpenExtract, an automated data extraction tool for literature reviews. It uses large language models (LLMs) to efficiently extract data from scientific articles, achieving high accuracy.
Area of Science:
- Biomedical Informatics
- Digital Health
- Scientific Literature Analysis
Background:
- Systematic literature reviews require extensive data extraction.
- Manual data extraction is time-consuming and prone to errors.
- Automating this process can significantly improve efficiency and accuracy.
Purpose of the Study:
- To present OpenExtract, an open-source pipeline for automated data extraction.
- To evaluate the efficacy of OpenExtract in large-scale systematic literature reviews.
- To compare the performance of OpenExtract against human researchers.
Main Methods:
- Developed an open-source pipeline named OpenExtract.
- Utilized large language models (LLMs) to predict data entries from scientific articles.
- Applied OpenExtract to a systematic literature review in digital health.
- Compared OpenExtract's outputs with those of human researchers.
Main Results:
- OpenExtract achieved precision and recall scores greater than 0.8.
- Demonstrated effective and efficient automatic data extraction capabilities.
- Showed comparable performance to human researchers in data extraction tasks.
Conclusions:
- OpenExtract is an effective tool for automated data extraction in systematic literature reviews.
- The pipeline offers a significant improvement in efficiency and accuracy for large-scale reviews.
- OpenExtract shows promise for advancing digital health research through streamlined literature analysis.
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