Journal of Modern Medical

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Kashani M, Dastani M. Analysis of thematic trends in scientific publications of Iranian researchers in artificial intelligence for medical sciences: A scientometric study. JMIS 2024; 10 (3) :231-246
URL: http://jmis.hums.ac.ir/article-1-543-en.html

Introduction: Recognizing the rapid growth of AI research in medical sciences, the present study aims to examine and analyze the scientific publications of Iranian researchers in the field of artificial intelligence (AI) in medical sciences.
Methods: This applied study employed scientometric techniques and the construction of scientific collaboration networks to evaluate the scientific output of Iranian researchers in the field of AI and medical sciences. The data used in this study comprised relevant scientific publications from the WOSCC database. For data analysis, the Bibliometrix package of the R programming language and the Biblioshiny graphical interface were utilized.
Results: The findings reveal a substantial growth in the volume of scientific publications on AI in medical sciences in Iran, particularly in recent years. The peak years of 2023 and 2024 signify a significant milestone in this field. The scientific collaboration network among Iranian researchers is dispersed, with the United States, China, and Canada having the most international collaborations with Iranian researchers. Thematic analysis revealed that fundamental topics such as “machine learning” and “deep learning” are the foundation of research in the field. Additionally, emerging topics such as “personalized medicine” and “global optimization” have recently attracted more attention.
Discussion: To significantly advance AI and medical sciences in Iran, it is essential to strengthen scientific collaborations and prioritize high-impact research topics. By leveraging cutting-edge AI techniques, we can improve the quality and quantity of research output by Iranian researchers.