Sağlıkta yapay zekâ: Bibliyometrik bir analiz

Yıl 2024, Cilt: 11 Sayı: 2, 277 - 285, 30.06.2024

Tuba Gündüz Ferhat Eren

https://doi.org/10.52880/sagakaderg.1420580

Öz

Giriş ve Amaç: Yapay zekâ (YZ) veri, bilim ve teknolojinin ilerlemesiyle birlikte her alanda olduğu gibi sağlık alanındaki optimizasyon rolü dikkat çekmiştir. Bu bibliyometrik çalışma, sağlık alanındaki yapay zekâ odaklı araştırmaların ulusal literatürdeki genel durumunu değerlendirmeyi amaçlamaktadır. Gereç ve Yöntem: Bu doğrultuda ‘Türk Medline Ulusal Sağlık Bilimleri Süreli Yayınlar Veri Tabanı’ 13 Aralık 2023 tarihi itibariyle taranmış ve çalışmanın amacına uyan 290 çalışma bibliyometrik analize dahil edilip incelenmiştir. Bulgu ve Sonuç: Elde edilen veriler, sağlık alanındaki araştırmaların belirgin bir artış gösterdiğini ortaya koymaktadır. İncelenen çalışmalar, yabancı literatürde olduğu gibi kardiyoloji, üroloji, kanser ve nöroşirurji gibi uzmanlık alanlarının araştırmaların merkezine yerleştiğini göstermektedir. Ayrıca, hemşirelik ve diş sağlığı alanlarında gerçekleştirilen çalışmaların arttığı, bu sayede geniş bir uzmanlık yelpazesi içinde çeşitlenen araştırmalara tanıklık edildiği gözlemlenmiştir. Ek olarak çalışmaların genellikle çok yazarlı olması, ilgili alanın disiplinler arası özelliğine işaret etmektedir. Bununla birlikte, olgu-vaka-klinik türdeki uygulama odaklı çalışmaların göreceli olarak sınırlı olduğu bir bulgu ortaya çıkmıştır. Yabancı literatürden farklı olarak, etik, yasal ve güvenlik konularına yönelik yapılan çalışmaların neredeyse ihmal edildiği tespit edilmiştir. Bu bibliyometrik analiz, Türkiye'deki yapay zekâ temelli sağlık araştırmalarına geniş bir bakış açısı sunarak, sağlık alanındaki araştırmacılara, profesyonellere ve diğer paydaşlara değerli bir kaynak sağlama potansiyeline sahiptir.

Anahtar Kelimeler

Yapay Zekâ, Sağlık Araştırmaları, Bibliyometrik, Türkiye

Artificial intelligence in health: A bibliometric analysis

Öz

Introduction and Aim: With the advancement of artificial intelligence (AI) data, science and technology, its optimization role in the field of health has attracted attention as in every field. This bibliometric study aims to evaluate the general status of AI-oriented research in the health field in the national literature. Materials and Methods: Accordingly, 'Turkish Medline National Health Sciences Periodicals Database' was searched as of December 13, 2023 and 290 studies that fit the purpose of the study were included in the bibliometric analysis and examined. Findings and Conclusion: The data obtained reveal that there is a significant increase in research in the field of health. The reviewed studies show that specialties such as cardiology, urology, cancer and neurosurgery are at the center of research, as in foreign literature. In addition, it has been observed that the number of studies conducted in the fields of nursing and dental health has increased, thus witnessing diversified research in a wide range of specialties. In addition, the fact that the studies are generally multi-authored points to the interdisciplinary nature of the related field. However, it was also found that case-case-clinical practice-oriented studies were relatively limited. Unlike foreign literature, studies on ethical, legal and safety issues were almost neglected. This bibliometric analysis has the potential to provide a valuable resource to researchers, professionals and other stakeholders in the field of health by providing a broad perspective on AI-based health research in Turkey.

Anahtar Kelimeler

Artificial Intelligence, Health Research, Bibliometric, Turkey

Kaynakça

• Alloghani, M., Al-Jumeily, D., Aljaaf, A. J., Khalaf, M., Mustafina, J., & Tan, S. Y. (2019, September). The application of artificial intelligence technology in healthcare: a systematic review. In International conference on applied computing to support industry: Innovation and technology (pp. 248-261). Cham: Springer International Publishing.
• Alugubelli, R. (2016). Exploratory study of artificial intelligence in healthcare. International Journal of Innovations in Engineering Research and Technology, 3(1), 1-10.
• Amann, J., Blasimme, A., Vayena, E., Frey, D., Madai, V. I., & Precise4Q Consortium. (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC medical informatics and decision making, 20, 1-9.
• Artificial Intelligence. (29.12.2023). https://dictionary.cambridge.org/dictionary/english/artificial-intelligence Balagurunathan, Y., Mitchell, R., & El Naqa, I. (2021). Requirements and reliability of AI in the medical context. Physica Medica, 83, 72-78.
• Bindra, S., & Jain, R. (2023). Artificial intelligence in medical science: a review. Irish Journal of Medical Science (1971-), 1-11.
• Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2), 94.
• Dhamija, P., & Bag, S. (2020). Role of artificial intelligence in operations environment: a review and bibliometric analysis. The TQM Journal, 32(4), 869-896.
• Dicuonzo, G., Donofrio, F., Fusco, A., & Shini, M. (2023). Healthcare system: Moving forward with artificial intelligence. Technovation, 120, 102510.
• Guest. (21.02.2023). A digital health ecosystem for the world. Financial Express. https://www.financialexpress.com/opinion/a-digital-health-ecosystem-for-the-world/3217805/
• Guo, Y., Hao, Z., Zhao, S., Gong, J., & Yang, F. (2020). Artificial intelligence in health care: bibliometric analysis. Journal of Medical Internet Research, 22(7), e18228.
• Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism, 69, S36-S40. He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature medicine, 25(1), 30-36.
• Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4).
• Jimma, B. L. (2023). Artificial intelligence in healthcare: A bibliometric analysis. Telematics and Informatics Reports, 100041.
• Lee, J. C. (2019). The perils of artificial intelligence in healthcare: Disease diagnosis and treatment. Journal of Computational Biology and Bioinformatics Research, 9(1), 1-6.
• Lohr, S. (16.07.2021). IBM Is Counting on Its Bet on Watson, and Paying Big Money for It. The New York Times. https://www.nytimes.com/2016/10/17/technology/ibm-is-counting-on-its-bet-on-watson-and-paying-big-money-for-it.html
• Marr, B. (27.07.2018). How Is AI Used In Healthcare - 5 Powerful Real-World Examples That Show The Latest Advances. Forbes. https://www.forbes.com/sites/bernardmarr/2018/07/27/how-is-ai-used-in-healthcare-5-powerful-real-world-examples-that-show-the-latest-advances/?sh=7c67bdbf5dfb
• Morley, J., & Floridi, L. (2019). NHS AI Lab: why we need to be ethically mindful about AI for healthcare. Available at SSRN 3445421.
• Noorbakhsh-Sabet, N., Zand, R., Zhang, Y., & Abedi, V. (2019). Artificial intelligence transforms the future of health care. The American journal of medicine, 132(7), 795-801.
• Punith Kumar, C. R., Natarajan, R., Padma, K., & Sivaperuman, A. (2022). Artıfıcıal Intellıgence In Healthcare: A Brıef Revıew. Suranaree Journal of Science & Technology, 29(2).
• Rong, G., Mendez, A., Assi, E. B., Zhao, B., & Sawan, M. (2020). Artificial intelligence in healthcare: review and prediction case studies. Engineering, 6(3), 291-301.
• Saheb, T., Saheb, T., & Carpenter, D. O. (2021). Mapping research strands of ethics of artificial intelligence in healthcare: a bibliometric and content analysis. Computers in Biology and Medicine, 135, 104660.
• Schönberger, D. (2019). Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications. Int. J. Law Inf. Technol., 27, 171-203.
• Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC medical informatics and decision making, 21, 1-23.
• Sunarti, S., Rahman, F. F., Naufal, M., Risky, M., Febriyanto, K., & Masnina, R. (2021). Artificial intelligence in healthcare: opportunities and risk for future. Gaceta Sanitaria, 35, S67-S70.
• Tekkeşin, A. İ. (2019). Artificial intelligence in healthcare: past, present and future. Anatol J Cardiol, 22(Suppl 2), 8-9.
• Thayyib, P. V., Mamilla, R., Khan, M., Fatima, H., Asim, M., Anwar, I., ... & Khan, M. A. (2023). State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary. Sustainability, 15(5), 4026.
• Tran, B. X., Vu, G. T., Ha, G. H., Vuong, Q. H., Ho, M. T., Vuong, T. T., ... & Ho, R. C. (2019). Global evolution of research in artificial intelligence in health and medicine: a bibliometric study. Journal of clinical medicine, 8(3), 360.
• WHO issues first global report on Artificial Intelligence (AI) in health and six guiding principles for its design and use. (28.06.2021). https://www.who.int/news/item/28-06-2021-who-issues-first-global-report-on-ai-in-health-and-six-guiding-principles-for-its-design-and-use
• Yıldız, E. (2022). Türkiye’de gebelik ve anestezi konulu yayınların bibliyometrik analizi. Black Sea Journal of Health Science, 5(1), 50-55.
• Yu, K. H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), 719-731.
• Ek Materyal https://doi.org/10.48623/aperta.263990