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Evaluating a Locally Deployed 20-Billion Parameter Large Language Model for Automated Abstract Screening in Systematic Reviews
2026-03-04
health informatics
Title + abstract only
View on medRxiv
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BackgroundSystematic reviews (SRs) are essential for evidence-based medicine but require extensive time and resources for abstract screening. Large language models (LLMs) offer potential for automating this process, yet concerns about data privacy, intellectual property protection, and reproducibility limit the use of cloud-based solutions in research settings. ObjectiveTo evaluate the performance of a locally deployed 20-billion parameter LLM for automated abstract screening in systematic revi...
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