Journal of Yeungnam Medical Science

Original articles

Medical Informatics
Barriers and opportunities in biobank utilization: insights from a 3-year repeated cross-sectional survey of the Female Breast and Genital Disease with Microbiome Biobank Network (FDMNet) in South Korea: Sangzin Ahn, Hwa Jin Cho, Mi-Seon Kang, An Na Seo, Lucia Kim, Kyung Un Choi, Mee Sook Roh, Eun-Young Kim; J Yeungnam Med Sci. 2025;42:46. Published online August 27, 2025; DOI: https://doi.org/10.12701/jyms.2025.42.46

1,116 View
68 Download

Abstract PDF Supplementary Material: Background
This study aimed to document the patterns, challenges, and opportunities for biobank utilization within the Female Breast and Genital Disease with Microbiome Biobank Network (FDMNet) in South Korea. Annual surveys (2022–2024) assessed researcher awareness, utilization patterns, barriers to access, research requirements, and interest in microbiome research.
Methods
Online questionnaires were distributed to staff members at five university hospitals participating in FDMNet. Data from 155 respondents across 3 years were analyzed using descriptive statistics for quantitative data. Qualitative feedback was examined using Uniform Manifold Approximation and Projection and natural language processing to identify the thematic clusters of user challenges.
Results
Despite high engagement with biobank resources (76% of the respondents), declining participation rates and interinstitutional collaborations were observed, particularly in 2024, amid the nationwide healthcare crisis. The major barriers to utilization included complex access procedures (31.0%), lack of process knowledge (23.9%), and concerns about Institutional Review Board approval (11.6%). Breast neoplasms (12.3%) and female genital neoplasms (11.0%) were the primary research interests, with blood (24.5%) and tissue (23.9%) samples being the most requested specimens. Most respondents (66.5%) expressed interest in microbiome research but reported insufficient knowledge.
Conclusion
These findings highlight the need for streamlined access procedures, improved researcher education, enhanced clinical data integration, and stronger governance structures to overcome existing barriers to biobank utilization. These insights can guide strategic improvements in biobank operations and resource allocation to serve the evolving needs of the research community better.

Medical Informatics
Large language model usage guidelines in Korean medical journals: a survey using human-artificial intelligence collaboration: Sangzin Ahn; J Yeungnam Med Sci. 2025;42:14. Published online December 11, 2024; DOI: https://doi.org/10.12701/jyms.2024.00794

6,799 View
195 Download
1 Web of Science
4 Crossref

Background
Large language models (LLMs), the most recent advancements in artificial intelligence (AI), have profoundly affected academic publishing and raised important ethical and practical concerns. This study examined the prevalence and content of AI guidelines in Korean medical journals to assess the current landscape and inform future policy implementation.
Methods
The top 100 Korean medical journals determined by Hirsh index were surveyed. Author guidelines were collected and screened by a human researcher and AI chatbot to identify AI-related content. The key components of LLM policies were extracted and compared across journals. The journal characteristics associated with the adoption of AI guidelines were also analyzed.
Results
Only 18% of the surveyed journals had LLM guidelines, which is much lower than previously reported in international journals. However, the adoption rates increased over time, reaching 57.1% in the first quarter of 2024. High-impact journals were more likely to have AI guidelines. All journals with LLM guidelines required authors to declare LLM tool use and 94.4% prohibited AI authorship. The key policy components included emphasizing human responsibility (72.2%), discouraging AI-generated content (44.4%), and exempting basic AI tools (38.9%).
Conclusion
While the adoption of LLM guidelines among Korean medical journals is lower than the global trend, there has been a clear increase in implementation over time. The key components of these guidelines align with international standards, but greater standardization and collaboration are needed to ensure the responsible and ethical use of LLMs in medical research and writing.

Citations

Citations to this article as recorded by

Sense and sensibility of article submission platforms are needed regarding verification of AI use: a stakeholders’ perspective
Jaime A. Teixeira da Silva, Joshua Wang
AI and Ethics.2025; 5(6): 6127. CrossRef
Large Language Models(LLMs) in Political Science Research: Analysis of Topical Trends and Usage Patterns
Inbok RHEE
The Korean Journal of International Relations.2025; 65(3): 257. CrossRef
Performance of large language models in fluoride-related dental knowledge: a comparative evaluation study of ChatGPT-4, Claude 3.5 Sonnet, Copilot, and Grok 3
Raju Biswas, Atanu Mukhopadhyay, Santanu Mukhopadhyay
Journal of Yeungnam Medical Science.2025; 42: 53. CrossRef
Role of Medical Editors in the Age of Generative Artificial Intelligence
Sun Huh
Healthcare Informatics Research.2025; 31(4): 317. CrossRef

First
Prev
Page of 1
Next
Last

Search