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.

Keywords: artificial intelligence; bibliometric; bibliometrix R; citeSpace; melanoma; vOSviewer.