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The ethics of using artificial intelligence in writing medical research papers
Shinae Yu, Hyunyong Hwang
Kosin Med J. 2025;40(4):270-279.   Published online December 31, 2025
DOI: https://doi.org/10.7180/kmj.25.141
  • 7,454 View
  • 123 Download
  • 1 Citations
Abstract PDFPubReader   ePub   
The rapid integration of large language models into medical publishing offers considerable potential for improving drafting efficiency but simultaneously raises substantial concerns regarding research integrity, accountability, and the reliability of the scientific record. Recent incidents in which artificial intelligence (AI) systems were listed as coauthors have prompted urgent regulatory revisions. In this review, we identify a global consensus that strictly prohibits AI authorship, as algorithms lack both moral agency and legal accountability. Transparency has emerged as an essential requirement, and undisclosed AI use is increasingly regarded as a form of ethical misconduct. Key risks include “hallucinations” (notably citation fabrication), algorithmic bias, and potential violations of privacy regulations (e.g., the Health Insurance Portability and Accountability Act) when protected health information is processed through cloud-based platforms. The analysis indicates that rigid prohibitions are operationally unenforceable, supporting instead a “human stewardship” model in which AI functions as a drafting scaffold subjected to rigorous human verification. AI represents a lasting transformation in medical writing that necessitates a shift from simple prohibition to structured governance. To preserve epistemic validity, we propose a framework built on task segmentation, mandatory cross-referencing of claims, and data sovereignty. Ultimately, AI must remain a transparent assistive tool, with full responsibility for the manuscript residing exclusively with the human investigator.

Citations

Citations to this article as recorded by  
  • The Strategic Imperative: Medical Writing in a Globalized Pharma Landscape for Enhanced Trust and Content Delivery
    Mitesh Hood
    International Journal of Digital Health and Telemedicine.2026;[Epub]     CrossRef
The ethics of using artificial intelligence in medical research
Shinae Yu, Sang-Shin Lee, Hyunyong Hwang
Kosin Med J. 2024;39(4):229-237.   Published online December 6, 2024
DOI: https://doi.org/10.7180/kmj.24.140
  • 65,535 View
  • 1,180 Download
  • 19 Citations
Abstract PDFPubReader   ePub   
The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Citations

Citations to this article as recorded by  
  • Anemia in young women: determinants and artificial intelligence-based management approaches
    Guttapalam Sireesha, D. Madhavi, A. M. Beulah, M. Niharika, C. Pradeepthi
    Frontiers in Artificial Intelligence.2026;[Epub]     CrossRef
  • SERS Meets Artificial Intelligence: A New Frontier in Cancer Diagnosis and Prognosis
    Noor ul Huda, Rana Zaki Abdul Bari, Muhammad Abdullah Javed, Muhammad Naeem Kiani, Yongdong Jin
    Analytical Chemistry.2026; 98(12): 8757.     CrossRef
  • The onco-bariatric paradigm: a tri-phasic metabolic obesity framework for synergizing glucagon-like peptide-1 receptor agonists and metabolic bariatric surgery
    Dong Jin Park, Yoonhong Kim, Dongjae Jeon, Young Suk Park, Kyung Won Seo, Ki Hyun Kim
    Kosin Medical Journal.2026; 41(1): 3.     CrossRef
  • Beyond the algorithm: embedding ethics for trustworthy AI in radiology and oncology
    Mónica Cano Abadía, Melanie Goisauf
    Frontiers in Digital Health.2026;[Epub]     CrossRef
  • Informed Consent in AI-Augmented Dentistry and Dental Research: A Scoping Review
    Tamara Mihut, Corina Marilena Cristache, Luminita Oancea, Victor Nimigean
    Dentistry Journal.2026; 14(6): 320.     CrossRef
  • Artificial Intelligence in Cervical Cytology: Opportunities and Limitations in Screening, Triage, and Diagnostic Support
    Agata Stanek-Widera, Jędrzej Borowczak, Dominik Skiba, Michel-Edwar Mickael, Marzena Łazarczyk, Mateusz Maniewski, Łukasz Szylberg, Andrey Bychkov, Piotr Religa
    Diagnostics.2026; 16(10): 1541.     CrossRef
  • Applications, Challenges, and Future Directions of Large Language Models in Health Care Communication: Scoping Review
    Jing Chang, Ruotong Peng, Xi Chen, Yishu Zhu, Ruting Miao, Zeng Cao, Hui Feng
    Journal of Medical Internet Research.2026; 28: e84726.     CrossRef
  • A survey on medical multimodal retrieval-augmented generation (RAG)
    Ruipeng Wang, Jian Wang, Yan Huang, Haiyang Guo, Junjie Pang
    High-Confidence Computing.2026; : 100415.     CrossRef
  • A Modular Evaluation of AI-Assisted Clinical Documentation
    Julien Delaunay, Maissaa Sarkis, Jordi Solé-Casals, Jordi Cusido
    Applied Sciences.2026; 16(14): 6961.     CrossRef
  • Integrating Artificial Intelligence in Orthopedic Care: Advancements in Bone Care and Future Directions
    Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli, Mouayad Masalkhi
    Bioengineering.2025; 12(5): 513.     CrossRef
  • Current Bioinformatics Tools in Precision Oncology
    Tesfaye Wolde, Vipul Bhardwaj, Vijay Pandey
    MedComm.2025;[Epub]     CrossRef
  • Case Report: Intranasal esketamine combined with a form of generative artificial intelligence in the management of treatment-resistant depression
    Alexandre Fraichot, Sophie Favre, Hélène Richard-Lepouriel
    Frontiers in Psychiatry.2025;[Epub]     CrossRef
  • Future Designs of Clinical Trials in Nephrology: Integrating Methodological Innovation and Computational Power
    Camillo Tancredi Strizzi, Francesco Pesce
    Sensors.2025; 25(16): 4909.     CrossRef
  • The revolutionary impact of artificial intelligence in orthopedics: comprehensive review of current benefits and challenges
    Salar Baghbani, Yoosef Mehrabi, Mohammad Movahedinia, Erfan Babaeinejad, Mohammadamin Joshaghanian, Shayan Amiri, Mostafa Shahrezaee
    Journal of Robotic Surgery.2025;[Epub]     CrossRef
  • Human-in-the-Loop Performance of LLM-Assisted Arterial Blood Gas Interpretation: A Single-Center Retrospective Study
    Sergio Ayala-De la Cruz, Paola Elizabeth Arenas-Hernández, María Fernanda Fernández-Herrera, Rebeca Alejandrina Quiñones-Díaz, Jorge Martín Llaca-Díaz, Erik Alejandro Díaz-Chuc, Diana Guadalupe Robles-Espino, Erik Alejandro San Miguel-Garay
    Journal of Clinical Medicine.2025; 14(18): 6676.     CrossRef
  • Applications, Challenges, and Prospects of Generative Artificial Intelligence Empowering Medical Education: Scoping Review
    Yuhang Lin, Zhiheng Luo, Zicheng Ye, Nuoxi Zhong, Lijian Zhao, Long Zhang, Xiaolan Li, Zetao Chen, Yijia Chen
    JMIR Medical Education.2025; 11: e71125.     CrossRef
  • Ética, empatia e IA: como equilibrar decisões automatizadas e julgamento clínico humanizado
    Iranildo Lopes de Oliveira, Rivana Ferreira de Souza, João Victor de Amorim Batista, Iara Costa Silvano, Ana Caroline Rocha de Melo Leite, Rodolfo de Melo Nunes
    Cuadernos de Educación y Desarrollo.2025; 17(10): e9794.     CrossRef
  • Machine learning in lupus nephritis: bridging prediction models and clinical decision-making towards personalized nephrology
    Diego Fernando Garcia-Bañol, Adrianny Mahelis Arias-Choles, Silvia Aldana-Peréz, Gustavo J. Aroca-Martínez, Carlos Guido Musso, Roberto Navarro-Quiroz, Alex Dominguez-Vargas, Henry J. Gonzalez-Torres
    Frontiers in Medicine.2025;[Epub]     CrossRef
  • Ethical Integration of Artificial Intelligence in Nursing Research: An Evidence-based Practice Project from Saudi Arabia
    Jennifer de Beer, Khulud Bababkr Mohammed, Joynalyn Barrios, Salma Elnajjar, Meead Fawaz Aldabahy, Vimela Moodley, Asma Almuntashiri, Maab Basha, Ashwag Othman Eissa, Wejdan Omar Barayan, Shonise Young
    Journal of Nursing Science and Professional Practice.2025; 2(4): 183.     CrossRef
KMJ : Kosin Medical Journal
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