Research hotspots and trends for Duchenne muscular dystrophy: a machine learning bibliometric analysis from 2004 to 2023 - Fang, Pingping; Han, Jingzhe; An, Di; Bu, Yi; Ji, Guang; Liu, Mingjuan; Deng, Jinliang; Guo, Moran; Han, Xu; Wu, Hongran; Ma, Shaojuan; Song, Xueqin (Frontiers in Immunology, 2024)
AimsThe aim of this study was to conduct a bibliometric analysis of the relevant literature on Duchenne muscular dystrophy (DMD) to ascertain its current status, identify key areas of research and demonstrate the evolution of the field.MethodsThe analysis sourced documents from the Science Citation Index Expanded in the Web of Science core collection, utilizing CiteSpace software and an online bibliometric platform to analyze collaborative networks among authors, institutions and countries, and to map out the research landscape through journal and reference evaluations. Keyword analyses, including clustering and emergent term identification, were conducted, alongside the development of knowledge maps.ResultsThe study included 9,277 documents, indicating a rising publication trend in the field. The Institut National de la Santé et de la Recherche Médicale emerged as the top publishing institution, with Francesco Muntoni as the most prolific author. The United States dominated in publication output, showcasing significant leadership. The keyword analysis highlighted 786 key emergent terms, primarily focusing on the mechanisms, diagnostics and treatment approaches in DMD.ConclusionThe field of DMD research is experiencing robust growth, drawing keen interest globally. A thorough analysis of current research and trends is essential for advancing knowledge and therapeutic strategies in this domain.