Use of Generative AI in Medical Writing by Non-Native English Researchers

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Published Mar 30, 2025
https://doi.org/10.62438/tunismed.v103i4.5548
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Vol. 103 No. 4 (2025): Tunis Med Apr 2025

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Hamza Gazzeh
Research Laboratory LR19SP01, Sahloul Hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Tunisia
Amal Ghribi
Research Laboratory LR19SP01, Directorate of Information Systems, Sahloul Hospital of Sousse, Faculty of Medicine of Sfax, University of Sfax, Tunisia
Youssef Zanina
Research Laboratory LR19SP01, Directorate of Information Systems, Sahloul Hospital of Sousse, Faculty of Pharmacy of Monastir, University of Monastir, Tunisia
https://orcid.org/0000-0003-3921-3954
Mohamed Khelil
Research Laboratory LR19SP01, Directorate of Information Systems, Sahloul Hospital of Sousse, Tunisia
Ahmed Ben Abdelaziz
Research Laboratory LR19SP01, Directorate of Information Systems,Sahloul Hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Tunisia

Abstract

Introduction: Generative Artificial Intelligence (AI) has increasingly found its way into scientific medical writing, which can be particularly inappropriate in non-native English-speaking countries. This study aimed to determine the occurrence of AI-generated texts in medical publications originating from the Greater Maghreb countries (Libya, Tunisia, Algeria, Morocco, and Mauritania).


Methods: This was a cross-sectional study that gathered all medical publications indexed on MEDLINE, published in the first week of July 2024, with first author affiliated with Greater Maghreb countries. The rate of AI-generated texts was calculated using the AI detection tool: ZeroGPT®. Each article was analyzed in its entirety and each section separately (Abstract, Introduction, Methods, Results, and Discussion). Articles or sections were considered “suspects of AI generation” (sAI-g) if the rate was ≥25%. Results were presented as medians associated with their corresponding Inter Quartile Range (IQR).


Results: In all, 48 scientific medical articles were published by first authors from the Greater Maghreb countries. Articles were classified as “sAI-g” in 65% of cases, with a median rate of 36.2%[IQR=11.0%-49.4%]. AI-generated text was detected mainly in three sections: “Methods” (sAI-g=86%, median=59.3%[IQR=28.5%-71.7%]), “Abstract” (sAI-g=69%, median=52.2% [IQR=0.0%-90.2%]) and “Introduction” (sAI-g=58%, median=43.2%,[IQR=0.0%-79.4%]), while the "Discussion" section had the lowest median rate (sAI-g=30%, median=10.4%,[IQR=0.0%-27.9%]). 


Conclusion: Scientific medical articles from the Greater Maghreb countries used Generative AI extensively. This requires, on one hand, advancing medical education and mandating dissertations in English to build capacities for non-native English-speaking researchers, and on the other hand, providing training on the responsible use of AI  ..(abstract truncated at 250 words).

Keywords:

Generative Artificial Intelligence, ChatGPT , Chatbot , Large Language Models , Communication Barriers , Language Barriers, Medical Writing , Publication , Scientific Misconduct

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