Previously submitted to: JMIR Nursing (no longer under consideration since Dec 08, 2025)
Date Submitted: Nov 3, 2025
Open Peer Review Period: Nov 5, 2025 - Dec 8, 2025
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Machine Learning in Nursing: a concept analysis with Walker and Avant’s approach
ABSTRACT
Background:
Machine learning, as a subfield of artificial intelligence, can have extensive nursing applications. Accurate understanding of the concept of machine learning, ethical considerations, acceptance and efficiency of this technology in nursing are among the important issues that are examined.
Objective:
To analyze the various dimensions of the concept of Machine Learning in nursing and to delineate its boundaries from other related concepts in the field of artificial intelligence.
Methods:
This study employs a conceptual analysis of machine learning in nursing, using the eight-step approach proposed by Walker and Avant. To fulfill key stages of this process, a search was conducted in several databases, including CINAHL, Embase, Scopus, PubMed, and Web of Science, using MeSH terms that focus on the keywords "machine learning" and "nursing" in articles published in English between 2018 and 2025.
Results:
The defining characteristics of machine learning include data-driven approaches, automation of the learning process, pattern extraction and relationship detection, algorithmic diversity, and adaptability. By leveraging these features, machine learning can optimize care processes, leading to an enhancement in the quality of nursing services. Machine learning models have the capability to identify disease trends, risk factors, and vital changes in patients' conditions, thereby facilitating the provision of preventive care. However, despite its significant potential to improve care quality, machine learning faces profound challenges in implementation and acceptance within clinical settings.
Conclusions:
Machine learning has the potential to enhance the quality of nursing care. However, challenges such as the limitations of models in generalizing to diverse populations, ethical concerns regarding privacy, and resistance to technology adoption necessitate integrated solutions.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.