Global trends, collaboration networks and knowledge mapping of artificial intelligence evolution in sepsis diagnosis and management: A bibliometric analysis

Objective Sepsis remains a critical global healthcare challenge with high mortality rates, where traditional diagnostics lack sensitivity and standardized treatments show limited efficacy due to patient variability. While artificial intelligence (AI) has advanced sepsis diagnosis and management, systematic bibliometric analyses are scarce, particularly regarding recent research trends from 2022 to 2025. This study aims to reveal research development patterns and frontier dynamics of AI applications in sepsis diagnosis and management, providing strategic guidance and decision support for researchers, clinicians, and policymakers in this rapidly evolving field. Methods Web of Science data related to AI in sepsis published from 2005 to 2025 were retrieved. Multidimensional bibliometric and visualization analyses were conducted using VOSviewer, CiteSpace, and Bibliometrix packages. Results AI applications in sepsis research demonstrated exponential growth since 2016, peaking at 352 publications and 1363 citations in 2024. The United States dominates both publication volume (487 papers) and citation impact (12,984 citations), while China ranks second in output (457 papers) but shows significantly lower impact (3929 citations). Research clustered into six major directions encompassing intelligent prediction, molecular mechanisms, and deep learning early warning systems. Post-2022 analysis revealed emerging keywords including “ARDS (Acute Respiratory Distress Syndrome),” “MIMIC-IV,” and “immune infiltration,” signaling shifts toward multi-omics integration and precision medicine. The most highly cited studies focused on sepsis phenotypic subtyping (776 citations) and AI treatment strategies (619 citations). Conclusion AI applications in sepsis research are transitioning from algorithm validation toward clinical application, developing in the direction of explainable AI and precision sepsis care. The research trajectory evolves from “proof of concept” toward “ensuring clinical utility.” These findings provide strategic guidance for healthcare systems, highlighting the importance of interpretable models, multi-center validation, and infrastructure development for next-generation precision sepsis management.