Source: Research synthesis methods [Res Synth Methods] 2025 Nov; Vol. 16 (6), pp. 859-875. Date of Electronic Publication: 2025 Jun 23.Publisher: Wiley Blackwell Country of Publication: England NLM ID: 101543738 Publication Model: Print-Electronic Cited Medium: Internet ISSN:

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Generalizable and scalable multistage biomedical concept normalization leveraging large language models

Authors : Nicholas J. Dobbins

Subjects: FOS: Computer and information sciences; Computer Science - Computation and Language; Biomedical Research

Source: Res Synth Methods

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Academic Journal

Validation of large language models (Llama 3 and ChatGPT-4o mini) for title and abstract screening in biomedical systematic reviews

Authors : López-Pineda, Adriana; Nouni-García, Rauf; Carbonell-Soliva, Álvaro

Subjects: Likelihood Functions; Biomedical Research; Abstracting and Indexing

Source: Res Synth Methods

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Zero- and Few-Shot Prompting of Generative Large Language Models Provides Weak Assessment of Risk of Bias in Clinical Trials

Authors : Simon Šuster (ORCID 0000-0002-8817-8545); Timothy Baldwin; Karin Verspoor (ORCID 0000-0002-8661-1544)

Subjects: Medical Research; Safety; Experimental Groups

Source: Research Synthesis Methods. 2024 15(6):988-1000.13

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Performance of Two Large Language Models for Data Extraction in Evidence Synthesis

Authors : Amanda Konet (ORCID 0000-0001-5295-6483); Ian Thomas; Gerald Gartlehner (ORCID 0000-0001-5531-3678)

Subjects: Data Collection; Artificial Intelligence; Computer Software

Source: Research Synthesis Methods. 2024 15(5):818-824.7

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Can Large Language Models Replace Humans in Systematic Reviews? Evaluating GPT-4's Efficacy in Screening and Extracting Data from Peer-Reviewed and Grey Literature in Multiple Languages

Authors : Qusai Khraisha (ORCID 0000-0002-4664-1204); Sophie Put; Johanna Kappenberg

Subjects: Peer Evaluation; Research Reports; Artificial Intelligence

Source: Research Synthesis Methods. 2024 15(4):616-626.11

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فلترة النتائج

Compact large language models for title and abstract screening in systematic reviews: An assessment of feasibility, accuracy, and workload reduction

Using large language models to directly screen electronic databases as an alternative to traditional search strategies such as the Cochrane highly sensitive search for filtering randomized controlled trials in systematic reviews

StudyTypeTeller—Large language models to automatically classify research study types for systematic reviews

Assessing risk of bias of cohort studies with large language models

Optimal large language models to screen citations for systematic reviews.

Generalizable and scalable multistage biomedical concept normalization leveraging large language models

Validation of large language models (Llama 3 and ChatGPT-4o mini) for title and abstract screening in biomedical systematic reviews

Zero- and Few-Shot Prompting of Generative Large Language Models Provides Weak Assessment of Risk of Bias in Clinical Trials

Performance of Two Large Language Models for Data Extraction in Evidence Synthesis

Can Large Language Models Replace Humans in Systematic Reviews? Evaluating GPT-4's Efficacy in Screening and Extracting Data from Peer-Reviewed and Grey Literature in Multiple Languages

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