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Updated: Jan 14, 2026

Semi-automated Analysis of Mouse Skeletal Muscle Morphology and Fiber-type Composition
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Using Artificial Intelligence for Scholarly Writing.

Marilyn H Oermann1, Jacqueline K Owens, Heather Carter-Templeton

  • 1Marilyn H. Oermann is Thelma M. Ingles Professor of Nursing at the Duke University School of Nursing, Durham, NC, and editor-in-chief, Nurse Educator. Jacqueline K. Owens is professor emerita at the Ashland University Schar College of Nursing and Health Sciences, Grafton, OH, and editor-in-chief, OJIN: The Online Journal of Issues in Nursing. Heather Carter-Templeton is associate professor at the West Virginia University School of Nursing, Morgantown, and editor, CIN: Computers, Informatics, Nursing. Gabriel Peterson is associate professor at the North Carolina Central University School of Library and Information Sciences, Durham. Hannah E. Bailey is a data analyst at Data Driven WV, West Virginia University, Morgantown. Contact author: Marilyn H. Oermann, marilyn.oermann@duke.edu. The authors have disclosed no potential conflicts of interest, financial or otherwise.

The American Journal of Nursing
|October 23, 2025
PubMed
Summary
This summary is machine-generated.

Generative artificial intelligence (genAI) offers benefits for scholarly writing but requires responsible use. Nurse authors must integrate their expertise and judgment with AI-generated content to ensure accuracy and integrity in publications.

Keywords:
AI biaschatbotsgenerative artificial intelligencescholarly communicationwriting for publication

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Area of Science:

  • Scholarly Communication
  • Artificial Intelligence in Research
  • Medical Writing

Background:

  • Generative artificial intelligence (genAI) tools are increasingly accessible, impacting scholarly communication.
  • Authors using genAI face new responsibilities regarding integrity and transparency.
  • Concerns include ethical issues, inaccurate content, and lack of accountability.

Purpose of the Study:

  • To provide an overview of research on genAI in scholarly writing.
  • To offer guidelines for nurse authors on the appropriate use of AI in manuscript preparation.
  • To address key issues such as authorship, accuracy, bias, plagiarism, and disclosure.

Main Methods:

  • Review of recent research findings on genAI in scholarly writing.
  • Development of guidelines for clinicians, educators, and nurse authors.
  • Analysis of ethical considerations and best practices for AI integration.

Main Results:

  • GenAI tools can assist in creating text, tables, and figures.
  • Essential to maintain authorial judgment and subject matter expertise.
  • Potential risks include ethical breaches, inaccurate or biased content, and plagiarism.

Conclusions:

  • Nurse authors must critically evaluate and integrate AI-generated content with their expertise.
  • Transparency and disclosure of AI tool usage are crucial.
  • Adherence to guidelines ensures the integrity and credibility of scholarly communication.