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Bibliometric Analysis of Monte Carlo-Based Medical Physics Research in Korea (2015–2024)open access

Authors
Son, GaheeLee, Seok-HoYun, YongdoHan, Min CheolKim, Jin SungKim, Chan Hyeong
Issue Date
Dec-2025
Publisher
한국의학물리학회
Keywords
Monte Carlo; Medical physics; Bibliometrics; Research trend
Citation
PROGRESS in MEDICAL PHYSICS, v.36, no.4, pp 79 - 91
Pages
13
Indexed
KCI
Journal Title
PROGRESS in MEDICAL PHYSICS
Volume
36
Number
4
Start Page
79
End Page
91
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212514
DOI
10.14316/pmp.2025.36.4.79
ISSN
2508-4445
2508-4453
Abstract
This study analyzed Monte Carlo (MC)-based medical physics research in Korea between 2015–2024 with a focus on publication trends, research themes, and collaboration patterns. A bibliometric analysis of 310 publications that were retrieved from the Scopus and Google Scholar databases was performed. Here, publication trends, journal impact, and simulation toolkit usage were assessed quantitatively. In addition, co-occurrence and keyword network analyses were conducted to investigate thematic patterns. Moreover, author collaboration was examined institutionally and internationally. The findings of this study revealed steady research productivity, with annual publication outputs ranging from 25 to 40 papers and an increasing proportion of papers published in high-impact Science Citation Index Expanded-indexed journals (88.9%), representing a qualitative shift in publication strategies. Thematically, research in this field focuses on radiation dosimetry and medical imaging, with the widespread use of MC codes, e.g., Geant4 and its derivative toolkits in 54.7% of studies, as well as MC N-Particle (MCNP) in 13.2% of studies, across various clinical applications. A distinct feature of the Korean research environment is active domestic collaboration, which was observed in 51.0% of publications. In contrast, international collaboration remains comparatively limited (21.0%). Emerging topics, e.g., artificial intelligence (AI), have gained global attention; however, only 2.3% of Korean MC-based research incorporated AI-related approaches, reflecting a more conservative research focus than international trends. Korean MC-based medical physics research has maintained stable output, with an increasing emphasis on quality and clinical relevance. Promoting interdisciplinary research, fostering international collaboration, and integrating emerging technologies, e.g., AI, are essential to further advance the field and align it with global developments. These efforts are expected to enhance the precision and clinical utility of MC simulations and ensure continued progress in medical physics.
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