This paper is in the following e-collection/theme issue:

New Methods (1017) Generative Language Models Including ChatGPT (459) Artificial Intelligence (1660) Chatbots and Conversational Agents (614)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52758, first published .
Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews

Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews

Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews

Authors of this article:

Kentaro Matsui1, 2 Author Orcid Image ;   Tomohiro Utsumi2, 3 Author Orcid Image ;   Yumi Aoki4 Author Orcid Image ;   Taku Maruki5 Author Orcid Image ;   Masahiro Takeshima6 Author Orcid Image ;   Yoshikazu Takaesu7 Author Orcid Image
Article Authors Cited by (6) Tweetations (57) Metrics

Journals

  1. Oami T, Okada Y, Nakada T. GPT-3.5 Turbo and GPT-4 Turbo in Title and Abstract Screening for Systematic Reviews. JMIR Medical Informatics 2025;13:e64682 View
  2. Colangelo M, Guizzardi S, Meleti M, Calciolari E, Galli C. How to Write Effective Prompts for Screening Biomedical Literature Using Large Language Models. BioMedInformatics 2025;5(1):15 View
  3. Sanghera R, Thirunavukarasu A, El Khoury M, O’Logbon J, Chen Y, Watt A, Mahmood M, Butt H, Nishimura G, Soltan A. High-performance automated abstract screening with large language model ensembles. Journal of the American Medical Informatics Association 2025 View
  4. López-Pineda A, Nouni-García R, Carbonell-Soliva Á, Gil-Guillén V, Carratalá-Munuera C, Borrás F. Validation of large language models (Llama 3 and ChatGPT-4o mini) for title and abstract screening in biomedical systematic reviews. Research Synthesis Methods 2025:1 View
  5. Sujau M, Wada M, Vallée E, Hillis N, Sušnjak T. Accelerating Disease Model Parameter Extraction: An LLM-Based Ranking Approach to Select Initial Studies for Literature Review Automation. Machine Learning and Knowledge Extraction 2025;7(2):28 View
  6. Kobayashi Y, Uchida T, Kageyama I, Iwasaki Y, Ito R, Tsuda K, Akiyama H, Kodama K. Uncovering new psychoactive substances research trends using large language model-assisted text mining (LATeM). Journal of Hazardous Materials Advances 2025;18:100700 View