SavedAdd your journal

Journals / Ebelik ve Sağlık Bilimleri Dergisi / 2026 / Volume: 8 Issue: 3

Artificial Intelligence Applications in Nursing: A Bibliometric Analysis

Hemşirelikte Yapay Zeka Uygulamaları: Bir Bibliyometrik Analiz

Nurdan Yalçın Atar(Sağlık Bilimleri Üniversitesi Hemşirelik Fakültesi)0000-0002-6318-3882
Öznur Tuğba Çelebi Dursun(HALİÇ ÜNİVERSİTESİ)0000-0002-8228-4443
Pages
—
Publication Date
2025-09-29
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

To address healthcare challenges, organizations should support artificial intelligence research and integrate it into nursing education to enhance innovation and improve patient care.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Objective: This bibliometric analysis aimed to shed light on future research and offer a new perspective by examining the use of artificial intelligence in nursing from a broader perspective.
📊
Key Findings & Data:Studies containing the keywords "artificial intelligence", "machine learning" and "nursing" (n=32) were included.
💡
Conclusion & Impact:To address healthcare challenges, organizations should support artificial intelligence research and integrate it into nursing education to enhance innovation and improve patient care.
🔬Design:Modeling & Simulation
📍Scope:2000 Verileri
⚙️Variables:Artificial intelligence · bibliometric analysis · machine learning

Abstract

Objective: This bibliometric analysis aimed to shed light on future research and offer a new perspective by examining the use of artificial intelligence in nursing from a broader perspective. Methods: The Web of Science database was used to identify the relevant studies. Studies containing the keywords "artificial intelligence", "machine learning" and "nursing" (n=32) were included. While scanning, only studies in English and Turkish were considered, and only studies published between 2000 and 2023 were evaluated. Results: According to the publication years, 5 studies were conducted in 2019, 7 in 2020, 6 in 2021, 6 in 2022 and 5 in 2023. The main topics of the studies were management information systems, critical care, and oncology. Roschelle Fritz was identified as the most prolific author. The Journal of Nursing Management had the highest number of publications. Most artificial intelligence research in nursing has been conducted in the United States. Conclusion: Despite the recent growth, studies on artificial intelligence applications in nursing remain limited. To address healthcare challenges, organizations should support artificial intelligence research and integrate it into nursing education to enhance innovation and improve patient care.

Özet

Amaç: Bu bibliyometrik analiz, gelecekteki araştırmalara ışık tutmayı ve hemşirelikte yapay zekanın kullanımını daha geniş bir perspektiften inceleyerek yeni bir bakış açısı sunmayı amaçlamıştır. Yöntemler: İlgili çalışmaları belirlemek için Web of Science veri tabanı kullanılmıştır. Yapay zeka, makine öğrenimi ve hemşirelik anahtar kelimelerini içeren çalışmalar (n: 32) dahil edilmiştir. Tarama sırasında İngilizce ve Türkçe dilleri filtrelenmiş ve yalnızca 2000 ile 2023 yılları arasında yayınlanan çalışmalar değerlendirilmiştir. Bulgular: Yıllara göre 2019'da 5, 2020'de 7, 2021'de 6, 2022'de 6 ve 2023'te 5 çalışma yürütülmüştür. Çalışmanın konuları yönetim bilgi sistemleri, yoğun bakım ve onkolojidir. En üretken yazar Roschelle Fritz olarak belirlenmiştir. Journal of Management Nursing en fazla yayına sahip dergidir. Yapay zeka araştırmalarının çoğu Amerika Birleşik Devletleri'nde yürütülmüştür. Sonuç: Son yıllardaki artışa rağmen, hemşirelikte yapay zeka uygulamalarına yönelik çalışmaların sınırlı olduğu görülmektedir. Sağlık hizmetlerindeki zorlukların üstesinden gelmek için kurumlar, yapay zekâ araştırmalarını desteklemeli ve hemşirelik eğitimine entegre etmelidir.

🔖

Cite This Article

Atar, N. Y., Dursun, Ö. T. Ç. (2025). Artificial Intelligence Applications in Nursing: A Bibliometric Analysis. Ebelik ve Sağlık Bilimleri Dergisi, Volume: 8 Issue: 3. https://doi.org/10.62425/esbder.1624800

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (17)

  1. Akgerman, A., & Ozdemir Yavuz, E. (2022). Artificial intelligence and nursing. Journal of Artificial Intelligence in Health Sciences, 2(1), 21-27. https://doi.org/10.52309/jaihs.v2i1.36
  2. Alp, F., Isbay, B., & Oner, O. (2023). Bibliometric analysis of graduate theses on the use of artificial intelligence methods in the field of healthcare (2015–2022). Gevher Nesibe Journal of Medical and Health Sciences, 8(1), 228–237. https://doi.org/10.5281/zenodo.7602783
  3. Aria, M., & Cuccurullo, C. (2017) Bibliometrix: An R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  4. Bilgili, N., & Erdal, A. (2023). Nurses' technology use skills and acquisition of technological competencies in the context of telemedicine applications/telenursing care. Y. Kitis (Ed.), Remote Care Services and Technological Opportunities to Ensure Continuity of Health Care. 1st edition., Ankara: Türkiye Klinikleri, p.72-8.
  5. Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2021). Predicted influences of artificial intelligence on nursing education: A scoping review. JMIR Nursing, 4(1), e23933. https://doi.org/10.2196/23933
  6. Cetin, B., & Eroglu, N. (2020). The place of technology and innovation in nursing care. Acta Medica Nicomedia, 3, 1-10.
  7. Clipper, B. (2020). The influence of the COVID-19 pandemic on technology: adoption in health care. Nurse Leader, 18(5), 500–503. https://doi.org/10.1016/j.mnl.2020.06.008
  8. Coiera, E. (2003). Clinical decision support systems. Guide to Health Informatics, 2(1), 201-216.
  9. Demirkol, D., Kocoglu, F.O., Aktas, S., & Erol, C. A. (2022). Bibliometric analysis of the relationship between diabetes and artificial intelligence. J Ist Faculty Medical, 85(2), 249-57. https://doi.org/10.26650/IUITFD.928111
  10. Gaviria-Marin, M., Merigó, J. M., & Baier-Fuentes, H. (2019). Knowledge management: A global examination based on bibliometric analysis. Technological Forecasting and Social Change, 140, 194-220. https://doi.org/10.1016/j.techfore.2018.07.006
  11. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., & Ma, S. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, 2(4), 230–43. https://doi.org/10.1136/svn-2017-000101
  12. Kaynak, O. (2021). The golden age of artificial intelligence. Discover Artificial Intelligence, 1(1). https://doi.org/10.1007/s44163-021-00009-x
  13. Maddox, T.M., Rumsfeld, J.S., & Payne, P.R.O. (2019). Questions for artificial intelligence in health care. JAMA, 321(1), 31–2. https://doi.org/10.1001/jama.2018.18932
  14. Parlar, T., & Esen, F.S. (2023). A bibliometric analysis on the use of health informatics and artificial intelligence in the post-covid-19 period. Balkan and Near Eastern Journal of Social Sciences, 9(1), 75-83.
  15. Reddy, S., Fox, J., & Purohit, M.P. (2019). Artificial intelligence-enabled healthcare delivery. Journal of the Royal Society of Medical, 112(1), 22–8. https://doi.org/10.1177/0141076818815510
  16. Robert, N. (2019). How artificial intelligence is changing nursing. Nursing Management, 50(9), 30. https://doi.org/10.1097/01.numa.0000578988.56622.21
  17. van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.