โก Quick Summary
This bibliometric analysis highlights the rapid growth of Artificial Intelligence (AI) applications in melanoma research, with publications surging to 260 in 2024. The study emphasizes the need for future research to focus on explainable AI and cross-disciplinary collaboration to enhance clinical outcomes.
๐ Key Details
- ๐ Dataset: 1,476 articles/reviews from Web of Science Core Collection
- ๐ Leading countries: United States (337 publications), China (292 publications)
- ๐ซ Top institution: Germany
- ๐ Core journals: IEEE Access (57 publications), Diagnostics (54 publications)
- ๐ Research hotspots: AI-assisted diagnosis and AI-integrated immunotherapy
๐ Key Takeaways
- ๐ Publication growth in AI and melanoma research has accelerated since 2017.
- ๐ The United States and China are leading in research output.
- ๐ Germany stands out as the top institution for AI in melanoma studies.
- ๐ฐ IEEE Access and Diagnostics are key journals in this field.
- ๐ก AI-assisted diagnosis and AI-integrated immunotherapy are the main research focuses.
- ๐ Future research should prioritize diverse datasets and explainable AI.
- ๐ค Cross-disciplinary cooperation is essential for translating research into clinical practice.
๐ Background
Melanoma, recognized as one of the most lethal forms of skin cancer, poses significant challenges in terms of diagnosis and treatment. The integration of Artificial Intelligence (AI) into melanoma research offers promising avenues for improving early diagnosis, prognosis, and therapeutic strategies. However, a comprehensive bibliometric analysis of this emerging field has been lacking, highlighting the need for a detailed examination of publication trends and research hotspots.
๐๏ธ Study
This study conducted a thorough bibliometric analysis of 1,476 articles and reviews related to AI and melanoma, sourced from the Web of Science Core Collection. Utilizing tools such as VOSviewer, CiteSpace, and bibliometrix, the researchers analyzed co-authorship, citation patterns, keyword trends, and journal contributions to gain insights into the evolving landscape of this research area.
๐ Results
The findings revealed a remarkable increase in publications post-2017, culminating in 260 publications in 2024. The United States led the way with 337 publications, followed closely by China with 292 publications. Germany emerged as the top institution, while IEEE Access and Diagnostics were identified as core journals. Keyword analysis highlighted two primary research hotspots: AI-assisted diagnosis and AI-integrated immunotherapy.
๐ Impact and Implications
The explosive growth of AI in melanoma research signifies a transformative shift in how we approach this deadly disease. By leveraging AI technologies, researchers can enhance diagnostic accuracy and treatment efficacy, ultimately improving patient outcomes. The emphasis on explainable AI and cross-disciplinary collaboration will be crucial in bridging the gap between research findings and clinical application, paving the way for innovative solutions in melanoma management.
๐ฎ Conclusion
This bibliometric analysis underscores the significant advancements in AI applications within melanoma research since 2017. As the field continues to evolve, focusing on diverse datasets and fostering interdisciplinary partnerships will be vital for translating research into clinical practice. The future of melanoma treatment looks promising with the integration of AI technologies, and ongoing research will be essential to harness their full potential.
๐ฌ Your comments
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Artificial Intelligence in melanoma research: a bibliometric analysis.
Abstract
BACKGROUND: As one of the most lethal skin cancers, melanoma has encountered many obstacles in diagnosis and therapy. Artificial Intelligence (AI) can help improve early diagnosis, prognosis, and treatment of melanoma. However, there is a lack of detailed and accurate bibliometric analysis of the field.
METHODS: All publications were extracted from Web of Science Core Collection based on AI and melanoma terms. Bibliometric analysis was conducted on 1,476 articles/reviews by using VOSviewer, CiteSpace and bibliometrix for co-authorship, citation, keyword and journal analysis.
RESULTS: There was a sudden increase in publications each year after 2017 and reached 260 in 2024. The United States (337 publications) and China (292 publications) ranked top in publication productivity. Germany was the top institution and author country. IEEE Access (57 publications) and Diagnostics (54 publications) were core journals. The two most prominent research hotspots were AI-assisted diagnosis and AI-integrated immunotherapy according to the keyword analysis.
CONCLUSION: AI in melanoma research has exploded since 2017. It is recommended that future research focus on various datasets, explainable AI, and cross-disciplinary cooperation to promote the transformation of achievements into clinical practice.
Author: [‘Guo Y’, ‘Huang X’, ‘Chen F’, ‘Ma J’, ‘Lv Y’, ‘Yang T’, ‘Guo Q’, ‘Sun Y’]
Journal: Int J Surg
Citation: Guo Y, et al. Artificial Intelligence in melanoma research: a bibliometric analysis. Artificial Intelligence in melanoma research: a bibliometric analysis. 2025; (unknown volume):(unknown pages). doi: 10.1097/JS9.0000000000003879