Mapping the scientific landscape of robotic hernia repair: a bibliometric and topic modeling analysis of thematic transitions

Abstract Robotic hernia repair (RHR) has profoundly transformed modern surgery, yet it remains intensely debated. To understand this dynamic field, bibliometric analysis offers a powerful tool to evaluate its evolving research trends. Our study presents a comprehensive bibliometric and machine learning analysis of 1,503 publications from 2003 to 2025. The literature demonstrates a growth trend (R 2 = 0.96), characterized by initial latency (2003–2015), steady adoption (2016–2020) and a recent exponential explosion (2020–2025) peaking at 262 publications in 2025. The United States is the leading contributing nation ( n = 892), followed by Italy ( n = 98), Germany ( n = 71), and China ( n = 68). Key contributors include Kudsi OY, Malcher F, and Muysoms F, with Surgical Endoscopy serving as the predominant publication venue ( n = 203). Spatial and relational networks were mapped using VOSviewer and CiteSpace. Critically, Latent Dirichlet Allocation (LDA) topic modeling combined with principal component analysis (PCA) stratified the corpus into four major research domains comprising the anatomical spectrum, the balance between resource and risk management, hardware evolution and surgical education, and technical complexity coupled with high-level evidence. Longitudinal regression of thematic probabilities revealed a significant thematic transition in research emphasis from early hardware feasibility and technical exploration toward value-based evaluation. Current research priorities are increasingly focused on rigorous cost-effectiveness evaluation in high-risk populations together with the generation of high-quality randomized evidence. In conclusion, this multidimensional analysis illustrates how this field is increasingly guided by the interconnected domains of Evidence, Education and Economics, which align with established frameworks for sustainable surgical progress.