Introduction: In recent years, the field of artificial intelligence (AI) and medical sciences has faced an increase in scientific production, which indicates the development of this research field. Therefore, this study was conducted with the aim of analyzing the process of Iranian researchers' scientific publications in AI for medical sciences by employing text mining techniques .
Methods: The present work is an applied research and was conducted using text mining techniques, specifically the topic modeling algorithm. Data was extracted until August 24, 2024, using an appropriate search strategy in the WOS database. In addition, the Python programming language was used to analyze the textual data.
Results: According to the outcome of topic modeling on 572 data related to the Iranian researchers' scientific publications in AI for medical sciences, five main topic clusters were obtained, which respectively include "modeling and prediction in medical systems," "AI," "learning, and training," "diagnosis and modeling in digital medicine," "cancer diagnosis using deep learning,"and "modeling and classification of medical images ."
Conclusion: The focus of Iranian research in the field of AI in medical sciences is more towards applications that are directly related to the improvement of prediction and modeling of diseases and medical systems. In addition, the trend towards emerging issues, such as medical education and the use of AI for the development of educational skills, indicates attention to the wider applications of this technology in improving the quality of education and learning in medical sciences.