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Volume 18, Issue 2 (Iranian Journal of Breast Diseases 2025)
ijbd 2025, 18(2): 4-23 |
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Ethics code: IR.UMSHA.REC.1403.460
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Zarghani M, Ouchi A, Saniee N, Omidi Hedayat F. A Bibliometric Analysis of Iranian Research on the Application of Artificial Intelligence in Breast Cancer. ijbd 2025; 18 (2) :4-23
URL: http://ijbd.ir/article-1-1144-en.html
URL: http://ijbd.ir/article-1-1144-en.html
1- Document Center and Central Library, Medical Information Management, Hamadan University of Medical Sciences, Hamadan, Iran
2- Department of Medical Library and Information Science, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran ,aliochi061@gmail.com
3- Department of Medical Library and Information Sciences, School of Allied Medical Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
2- Department of Medical Library and Information Science, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran ,
3- Department of Medical Library and Information Sciences, School of Allied Medical Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
Abstract: (594 Views)
Introduction: In recent decades, the application of Artificial Intelligence (AI) in various aspects of cancer diagnosis, treatment, and prognosis has shown great promise. The present study aimed to assess the performance of Iranian scientific publications concerning the use of AI in breast cancer through bibliometric methods.
Methods: The research encompasses all scientific productions of Iranian scholars focusing on the application of AI in breast cancer, indexed in the Web of Science Science Citation Index-Expanded (WOS SCIE) database without time limitation. Bibliometric analysis was performed using Excel (version 2019), BiblioShiny, and VOS Viewer software.
Results: A total of 213 documents were retrieved from 929 authors. The results demonstrated a sustained growth trend in document production, with a growth rate of 3.06%, beginning in 2001 (n=1). Original articles were the predominant type of publication, with only a few single-author papers. “Ali Abbasian Ardakani” and the “Islamic Azad University” emerged as the author and institution with the highest scientific output, while “Computers in Biology and Medicine” was identified as the leading journal in this field. The co-authorship map indicated that Iranian researchers primarily collaborated with colleagues from the United States and China. “Deep learning” and “transfer learning” were highlighted as trending topics. In addition, “breast cancer,” “machine learning,” and “deep learning” emerged as the most frequent keywords.
Conclusion: This study offers a comprehensive overview of AI-related research in the field of breast cancer in Iran. It holds significant potential to aid researchers, policymakers, and specialists in advancing AI research relevant to this field and understanding its possible impacts.
Methods: The research encompasses all scientific productions of Iranian scholars focusing on the application of AI in breast cancer, indexed in the Web of Science Science Citation Index-Expanded (WOS SCIE) database without time limitation. Bibliometric analysis was performed using Excel (version 2019), BiblioShiny, and VOS Viewer software.
Results: A total of 213 documents were retrieved from 929 authors. The results demonstrated a sustained growth trend in document production, with a growth rate of 3.06%, beginning in 2001 (n=1). Original articles were the predominant type of publication, with only a few single-author papers. “Ali Abbasian Ardakani” and the “Islamic Azad University” emerged as the author and institution with the highest scientific output, while “Computers in Biology and Medicine” was identified as the leading journal in this field. The co-authorship map indicated that Iranian researchers primarily collaborated with colleagues from the United States and China. “Deep learning” and “transfer learning” were highlighted as trending topics. In addition, “breast cancer,” “machine learning,” and “deep learning” emerged as the most frequent keywords.
Conclusion: This study offers a comprehensive overview of AI-related research in the field of breast cancer in Iran. It holds significant potential to aid researchers, policymakers, and specialists in advancing AI research relevant to this field and understanding its possible impacts.
Type of Study: Research |
Subject:
Health informatics
Received: 2024/10/12 | Accepted: 2025/01/28 | Published: 2025/07/1
Received: 2024/10/12 | Accepted: 2025/01/28 | Published: 2025/07/1
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