Mapping Knowledge Landscapes and Emerging Trends in Artificial Intelligence for Antimicrobial Resistance: Bibliometric and Visualization Analysis

The study analyzed the knowledge landscape and development trends in artificial intelligence (AI) applications for antimicrobial resistance (AMR) research using the Web of Science Core Collection database. The analysis revealed significant annual growth in publications from 2014 to 2023, with the United States, China, and India being the leading contributors. Key bibliometric indicators included co-authorship patterns, keyword co-occurrence, and citation impact. The study identified six enduring research clusters from 2014 to 2024, including sepsis, artificial neural networks, antimicrobial resistance, antimicrobial peptides, drug repurposing, and molecular docking. The study highlights the importance of AI in enhancing drug discovery and providing strategic insights for future research.