Evidence map›Paper›PMID 40007584›Full record

ReviewFrontiers in medicine2025

The integration of AI in nursing: addressing current applications, challenges, and future directions.

Qiuying Wei, Songcheng Pan, Xiaoyu Liu, Mei Hong, Chunying Nong, Weiqi Zhang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

62 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Qiuying WeiAnesthesia Surgery Center, The First Affiliated Hospital of Guangxi Medical University, Naning, Guangxi, China.
Songcheng PanAnesthesia Surgery Center, The First Affiliated Hospital of Guangxi Medical University, Naning, Guangxi, China.
Xiaoyu LiuAnesthesia Surgery Center, The First Affiliated Hospital of Guangxi Medical University, Naning, Guangxi, China.
Mei HongAnesthesia Surgery Center, The First Affiliated Hospital of Guangxi Medical University, Naning, Guangxi, China.
Chunying NongAnesthesia Surgery Center, The First Affiliated Hospital of Guangxi Medical University, Naning, Guangxi, China.
Weiqi ZhangAnesthesia Surgery Center, The First Affiliated Hospital of Guangxi Medical University, Naning, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence is increasingly influencing healthcare, providing transformative opportunities and challenges for nursing practice. This review critically evaluates the integration of AI in nursing, focusing on its current applications, limitations, and areas that require further investigation. A comprehensive analysis of recent studies highlights the use of AI in clinical decision support systems, patient monitoring, and nursing education. However, several barriers to successful implementation are identified, including technical constraints, ethical dilemmas, and the need for workforce adaptation. Significant gaps in the literature are also evident, such as the limited development of nursing-specific AI tools, insufficient long-term impact assessments, and the absence of comprehensive ethical frameworks tailored to nursing contexts. The potential of AI to reshape personalized care, advance robotics in nursing, and address global health challenges is explored in depth. This review integrates existing knowledge and identifies critical areas for future research, emphasizing the necessity of aligning AI advancements with the specific needs of nursing. Addressing these gaps is essential to fully harness AI's potential while reducing associated risks, ultimately enhancing nursing practice and improving patient outcomes.

Indexed as

artificial intelligencehealthcareintegrationnursingnursing practice

Identifiers

PMID40007584
PMCPMC11850350

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.