The Importance of Information Systems and Artificial Intelligence Research in Biomedical, Analysis of All Publications in the Scopus Database with R Software

Öz

As technological advancements continue to exert influence across various facets of our daily existence, the significance of information systems and artificial intelligence is progressively escalating within the disipline of biomedical. The aim of the study is to analyze the studies biomedical and information systems and artificial intelligence. Informations were questioned by selecting article title, abstract, keywords using the Scopus database for analysis. As a result of the scanning, it was determined that there were 319 academic studies from 1976 to 2023. All studies were included in the bibliometric analysis. 4.3.1 of the R software for analysis. The bibliometric library of the version was used. The overview, sources, authors, documents, conceptual structure and social structure groups in the library were analyzed. The most published years are 2007 (20) 2008 (20) and 2006 (19). The most published journals Are Journal of Biomedical Informatics (15). The most published author is Demner-Fushman with 5 publications. The countries that publications the most are USA (59) The most cited countries are USA (1922). It was determined that 827 keywords were used. The most used keywords were determined as artificial intelligence (352).

Anahtar Kelimeler

• Artificial Intelligence
• Information Systems
• Biomedical
• Data Analysis

Kaynakça

1. Alexander, C. Y. (2006). Methods in biomedical ontology. Journal of biomedical informatics, 39(3), 252-266.
2. Bhatti, U. A., Huang, M., Wu, D., Zhang, Y., Mehmood, A., & Han, H. (2019). Recommendation system using feature extraction and pattern recognition in clinical care systems. Enterprise information systems, 13(3), 329-351.
3. Bunescu, R., Ge, R., Kate, R. J., Marcotte, E. M., Mooney, R. J., Ramani, A. K., & Wong, Y. W. (2005). Comparative experiments on learning information extractors for proteins and their interactions. Artificial intelligence in medicine, 33(2), 139-155.
4. Butte, A. J., & Kohane, I. S. (2006). Creation and implications of a phenome-genome network. Nature biotechnology, 24(1), 55-62.
5. Da Costa, C. A., Pasluosta, C. F., Eskofier, B., Da Silva, D. B., & da Rosa Righi, R. (2018). Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards. Artificial intelligence in medicine, 89, 61-69.
6. De Solla Price, D. J. (1963). Little science, big science--and beyond. Columbia University Press.
7. Enderle, J., & Bronzino, J. (Eds.). (2012). Introduction to biomedical engineering. Academic press. https://www.scopus.com/search avaliable 01.01.2024
8. Isaksson, A., Wallman, M., Göransson, H., & Gustafsson, M. G. (2008). Cross-validation and bootstrapping are unreliable in small sample classification. Pattern Recognition Letters, 29(14), 1960-1965.

9. Laudon, K., & Laudon, J. (2009). Management Information Systems: International Edition, 11/E. London, UK: Pearson Higher Education.
10. Mbunge, E. (2020). Integrating emerging technologies into COVID-19 contact tracing: Opportunities, challenges and pitfalls. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(6), 1631-1636.
11. Mishra, R., Bian, J., Fiszman, M., Weir, C. R., Jonnalagadda, S., Mostafa, J., & Del Fiol, G. (2014). Text summarization in the biomedical domain: a systematic review of recent research. Journal of biomedical informatics, 52, 457-467.
12. Pratt, W., Reddy, M. C., McDonald, D. W., Tarczy-Hornoch, P., & Gennari, J. H. (2004). Incorporating ideas from computer-supported cooperative work. Journal of biomedical informatics, 37(2), 128-137.
13. Virone, G., Noury, N., & Demongeot, J. (2002). A system for automatic measurement of circadian activity deviations in telemedicine. IEEE Transactions on Biomedical Engineering, 49(12), 1463-1469.
14. Yılmaz, A (2022). Yapay Zeka. Kodlab Yayın Dağıtım Yazılım Ltd. Şti. 10.Basım