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Delving Into PubMed Records: How AI-Influenced Vocabulary has Transformed Medical Writing since ChatGPT Cover

Delving Into PubMed Records: How AI-Influenced Vocabulary has Transformed Medical Writing since ChatGPT

By: Kentaro Matsui  
Open Access
|Dec 2025

References

  1. 1Biswas S. ChatGPT and the Future of Medical Writing. Radiology. 2023;307(2):e223312. DOI: 10.1148/radiol.223312
  2. 2Salvagno M, Taccone FS, Gerli AG. Can artificial intelligence help for scientific writing? Crit Care. 2023;27(1):75. DOI: 10.1186/s13054-023-04380-2
  3. 3Lin Z. Towards an AI policy framework in scholarly publishing. Trends Cogn Sci. 2024;28(2):8588. DOI: 10.1016/j.tics.2023.12.002
  4. 4Thorp HH. ChatGPT is fun, but not an author. Science. 2023;379(6630):313. DOI: 10.1126/science.adg7879
  5. 5Lin Z. Techniques for supercharging academic writing with generative AI. Nat Biomed Eng. 2024. DOI: 10.1038/s41551-024-01185-8
  6. 6Berdejo-Espinola V, Amano T. AI tools can improve equity in science. Science. 2023;379(6636):991. DOI: 10.1126/science.adg9714
  7. 7Hwang SI, Lim JS, Lee RW, et al. Is ChatGPT a “Fire of Prometheus” for Non-Native English-Speaking Researchers in Academic Writing? Korean J Radiol. 2023;24(10):95259. DOI: 10.3348/kjr.2023.0773
  8. 8Matsui K, Koda M, Yoshida K. Implications of Nonhuman “Authors”. Jama. 2023;330(6):566. DOI: 10.1001/jama.2023.10568
  9. 9Cheng H, Sheng B, Lee A, et al. Have AI-Generated Texts from LLM Infiltrated the Realm of Scientific Writing? A Large-Scale Analysis of Preprint Platforms. bioRxiv; 2024. pp. 202403. DOI: 10.1101/2024.03.25.586710
  10. 10Geng M, Trotta R. Is ChatGPT Transforming Academics’ Writing Style? arXiv preprint arXiv:240408627; 2024.
  11. 11Liang W, Zhang Y, Wu Z, et al. Quantifying large language model usage in scientific papers. Nat Hum Behav. 2024. DOI: 10.1038/s41562-025-02273-8
  12. 12Liang W, Izzo Z, Zhang Y, et al. Monitoring AI-modified content at scale: a case study on the impact of ChatGPT on AI conference peer reviews. Proceedings of the 41st International Conference on Machine Learning. Vienna, Austria: JMLR.org; 2024. pp. 29575620.
  13. 13Masukume G. The Impact of AI on Scientific Literature: A Surge in AI-Associated Words in Academic and Biomedical Writing. medRxiv; 2024. pp. 202405. DOI: 10.1101/2024.05.31.24308296
  14. 14Tudino G, Qin Y. A corpus-driven comparative analysis of AI in academic discourse: Investigating ChatGPT-generated academic texts in social sciences. Lingua. 2024;312:103838. DOI: 10.1016/j.lingua.2024.103838
  15. 15Geng M, Trotta R. Human-LLM Coevolution: Evidence from Academic Writing Findings of the Association for Computational Linguistics: ACL 2025. Vienna, Austria. Association for Computational Linguistics; 2025. pp. 1268996. DOI: 10.18653/v1/2025.findings-acl.657
  16. 16Kobak D, González-Márquez R, Horvát E, Lause J. Delving into LLM-assisted writing in biomedical publications through excess vocabulary. Sci Adv. 2025;11(27):eadt3813. DOI: 10.1126/sciadv.adt3813
  17. 17Gray A. ChatGPT “contamination”: estimating the prevalence of LLMs in the scholarly literature. arXiv preprint arXiv:240316887. 2024.
  18. 18Juzek TS, Ward ZB. Why Does ChatGPT “Delve” So Much? Exploring the Sources of Lexical Overrepresentation in Large Language Models. Proceedings of the 31st International Conference on Computational Linguistics. Abu Dhabi, UAE. Association for Computational Linguistics; 2025. pp. 6397411.
  19. 19Ouyang L, Wu J, Jiang X, et al. Training language models to follow instructions with human feedback. Proceedings of the 36th International Conference on Neural Information Processing Systems. New Orleans, LA, USA: Curran Associates Inc.; 2022. pp. 2773044.
  20. 20Bailey HE, Carter-Templeton H, Peterson GM, Oermann MH, Owens JK. Prevalence of Words and Phrases Associated With Large Language Model-Generated Text in the Nursing Literature. Computers, Informatics, Nursing: Cin. 2025;43(4). DOI: 10.1097/CIN.0000000000001237
  21. 21Yakura H, Lopez-Lopez E, Brinkmann L, Serna I, Gupta P, Rahwan I. Empirical evidence of Large Language Model’s influence on human spoken communication. arXiv preprint arXiv:240901754. 2024.
  22. 22Bao T, Zhao Y, Mao J, Zhang C. Examining linguistic shifts in academic writing before and after the launch of ChatGPT: a study on preprint papers. Scientometrics. 2025;130(7):3597627. DOI: 10.1007/s11192-025-05341-y
  23. 23Peña Cáceres O, Sánchez-Rogel E, Barros-Naranjo J, Silva-Marchan H, Espinoza-Nima R, Correa-Calle T. Linguistic and Visual Patterns of ChatGPT in Higher Education: An Analysis of its Use in Undergraduate Theses. VISUAL REVIEW International Visual Culture Review/Revista Internacional de Cultura Visual. 2025;17(3):26578. DOI: 10.62161/revvisual.v17.5403
  24. 24Galpin R, Anderson B, Juzek TS. Exploring the Structure of AI-Induced Language Change in Scientific English. The International FLAIRS Conference Proceedings. 2025;38(1). DOI: 10.32473/flairs.38.1.138958
  25. 25Uribe SE, Maldupa I. Estimating the use of ChatGPT in dental research publications. Journal of Dentistry. 2024;149:105275. DOI: 10.1016/j.jdent.2024.105275
  26. 26Astarita S, Kruk S, Reerink J, Gómez P. Delving into the utilisation of chatgpt in scientific publications in astronomy. arXiv preprint arXiv:240617324; 2024.
  27. 27Qi H, Pan F. Lexical bundle variation across moves in abstracts of medical research articles. Southern African Linguistics and Applied Language Studies. 2020;38(2):10928. DOI: 10.2989/16073614.2020.1763814
  28. 28Iglewicz B, Hoaglin DC. How to Detect and Handle Outliers. ASQC Quality Press; 1993.
  29. 29Burns CS, Shapiro RM, Nix T, Huber JT. Search results outliers among MEDLINE platforms. Journal Of The Medical Library Association: Jmla. 2019;107(3):36473. DOI: 10.5195/jmla.2019.622
  30. 30Burns CS, Nix T, Shapiro RM, Huber JT. MEDLINE search retrieval issues: A longitudinal query analysis of five vendor platforms. Plos One. 2021;16(5):e0234221. DOI: 10.1371/journal.pone.0234221
  31. 31Dodge J, Sap M, Marasović A, et al. Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Online and Punta Cana, Dominican Republic: Association for Computational Linguistics; 2021. pp. 1286305. DOI: 10.18653/v1/2021.emnlp-main.98
  32. 32Al-Qudimat AR, Fares ZE, Elaarag M, Osman M, Al-Zoubi RM, Aboumarzouk OM. Advancing Medical Research Through Artificial Intelligence: Progressive and Transformative Strategies: A Literature Review. Health Science Reports. 2025;8(2):e70200. DOI: 10.1002/hsr2.70200
  33. 33Noll R, Berger A, Kieu D, et al. Assessing GPT and DeepL for terminology translation in the medical domain: A comparative study on the human phenotype ontology. Bmc Medical Informatics And Decision Making. 2025;25(1):237. DOI: 10.1186/s12911-025-03075-8
  34. 34Brglez M, Vintar Š. Lexical Diversity in Statistical and Neural Machine Translation. Information. 2022;13(2):93. DOI: 10.3390/info13020093
  35. 35Dizon G, Gayed JM. Examining the impact of Grammarly on the quality of mobile L2 writing. The JALT CALL Journal. 2021;17(2):7492. DOI: 10.29140/jaltcall.v17n2.336
  36. 36Abu Qub’a A, Abu Guba MN, Fareh S. Exploring the use of grammarly in assessing English academic writing. Heliyon. 2024;10(15):e34893. DOI: 10.1016/j.heliyon.2024.e34893
  37. 37Toral A. Post-editese: an Exacerbated Translationese Proceedings of Machine Translation Summit XVII: Research Track. Dublin, Ireland. European Association for Machine Translation; 2019. pp. 27381.
  38. 38Fu Y, Nederhof M-J. Automatic Classification of Human Translation and Machine Translation: A Study from the Perspective of Lexical Diversity. Proceedings for the First Workshop on Modelling Translation: Translatology in the Digital Age. online: Association for Computational Linguistics; 2021. pp. 9199.
  39. 39Niu J, Jiang Y. Does simplification hold true for machine translations? A corpus-based analysis of lexical diversity in text varieties across genres. Humanities and Social Sciences Communications. 2024;11(1):480. DOI: 10.1057/s41599-024-02986-7
  40. 40Park M, Leahey E, Funk RJ. Papers and patents are becoming less disruptive over time. Nature. 2023;613(7942):13844. DOI: 10.1038/s41586-022-05543-x
  41. 41Herbold S, Hautli-Janisz A, Heuer U, Kikteva Z, Trautsch A. A large-scale comparison of human-written versus ChatGPT-generated essays. Sci Rep. 2023;13(1):18617. DOI: 10.1038/s41598-023-45644-9
DOI: https://doi.org/10.5334/pme.1929 | Journal eISSN: 2212-277X
Language: English
Submitted on: Jun 3, 2025
Accepted on: Oct 17, 2025
Published on: Dec 2, 2025
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Kentaro Matsui, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.