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

New Methods (1139) Generative Language Models Including ChatGPT (721) Artificial Intelligence (2154) Chatbots and Conversational Agents (748)

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 (19) Tweetations (102) 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;32(5):893 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;16(4):620 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
  7. Clark J, Barton B, Albarqouni L, Byambasuren O, Jowsey T, Keogh J, Liang T, Moro C, O’Neill H, Jones M. Generative artificial intelligence use in evidence synthesis: A systematic review. Research Synthesis Methods 2025;16(4):601 View
  8. Trad F, Yammine R, Charafeddine J, Chakhtoura M, Rahme M, El-Hajj Fuleihan G, Chehab A. Streamlining systematic reviews with large language models using prompt engineering and retrieval augmented generation. BMC Medical Research Methodology 2025;25(1) View
  9. Vallamchetla S, Abdelkader O, Elnaggar A, Ramadan D, Islam Shourav M, Riaz I, Lin M. Do it faster with PICOS: Generative AI-Assisted systematic review screening. Journal of Biomedical Informatics 2025;168:104860 View
  10. Adel A, Alani N. Can generative AI reliably synthesise literature? exploring hallucination issues in ChatGPT. AI & SOCIETY 2025;40(8):6799 View
  11. Oami T, Okada Y, Nakada T. Optimal large language models to screen citations for systematic reviews. Research Synthesis Methods 2025;16(6):859 View
  12. Bayani A, Epoh Ewane L, Oliveira dos Anjos D, Mac-Seing M, Nikiema J. Leveraging open-source large language models (LLMs) in scoping reviews: a case study on disability and AI applications. International Journal of Medical Informatics 2025;204:106048 View
  13. Xu S, Zhao Z, Liu X, Meng X. A comparative study of screening performance between abstrackr and GPT models: Systematic review and contextual analysis. BMC Medical Informatics and Decision Making 2025;25(1) View
  14. Ito Y, Ikehara H, Okamoto Y, Kako J. Is Large Language Model-Assisted Citation Screening Feasible in a Scoping Review on Nonpharmacological Interventions for Delirium in Patients With Cancer?. Cureus 2025 View
  15. Rashid M, Yi C, Sathapanasiri T, Udayachalerm S, Boonpattharatthiti K, Insuk S, Veettil S, Lai N, Chaiyakunapruk N, Dhippayom T, Rashid M, Cheng S, Ming Lai N, Lawin S, Limhensin P, Wechkunanukul K, Mayang N, Rattanachaisit N, Ye X. Role of Generative Artificial Intelligence in Assisting Systematic Review Process in Health Research: A Systematic Review. Value in Health 2025;28(11):1665 View
  16. Li H, Wu X. The use of generative AI tools in academic writing: a systematic review of research trends and thematic insights. AI and Ethics 2025;5(6):5821 View
  17. Janoudi G, Uzun M, Disher T, Jurdana M, Fuzul E, Ivkovic J, Hutton B. Validating Loon Lens 1.0 for Autonomous Abstract Screening and Confidence-Guided Human-in-the-Loop Workflows in Systematic Reviews. Value in Health 2025;28(11):1630 View
  18. Cheng P, Hu F, Chen L, Liu J, Wu J, Chen W. Generative artificial intelligence in ophthalmology research writing: A comprehensive review of applications, detection tools, and ethical considerations. Taiwan Journal of Ophthalmology 2025 View
  19. Cassell K, Ologunowa A, Rastegar-Mojarad M, Chun B, Huang Y, Wang D, Cossrow N. Analysis of article screening and data extraction performance by an AI systematic literature review platform. Frontiers in Artificial Intelligence 2025;8 View