AI for Extracting Pre-Analytical Variability Data from Biomedical Literature: Feasibility and Validation.

Targeted token reduction significantly improved extraction quality. Overall, the study shows that LLMs can serve as effective tools for supporting structured data extraction in biomedical contexts-though current limitations in reproducibility and contextual fidelity highlight the continued need for expert oversight.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2025-09-03
DOI
https://doi.org/10.3233/shti251379
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI for Extracting Pre-Analytical Variability Data from Biomedical Literature: Feasibility and Validation.

Oliver J. Bott, Thomas Illig, Vicky Scholz, Sven Bichtemann et al.
PubMed
Biomedical Text Mining and Ontologies
article

AI for Extracting Pre-Analytical Variability Data from Biomedical Literature: Feasibility and Validation.

Oliver J. Bott, Thomas Illig, Vicky Scholz, Sven Bichtemann, Sara Haag
article en

Abstract

Targeted token reduction significantly improved extraction quality. Overall, the study shows that LLMs can serve as effective tools for supporting structured data extraction in biomedical contexts-though current limitations in reproducibility and contextual fidelity highlight the continued need for expert oversight.

PubMedVol. 331
Leibniz University Hannover (DE)
Openalex Percentile: Top 79%
Biomedical Text Mining and Ontologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.