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Semi-automated Analysis of Mouse Skeletal Muscle Morphology and Fiber-type Composition

Semi-automated Analysis of Mouse Skeletal Muscle Morphology and Fiber-type Composition

Published on: August 31, 2017

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

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 bias chatbots generative artificial intelligence scholarly communication writing 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.