(untitled) (NTU Journal of Engineering and Technology, 2026)
To examine key areas and emerging directions in artificial Intelligence (AI) research correlated to Antibiotic resistance. Research literature on AI in the field of Antibiotic resistance was gathered from the Science Citation Index expanded, which is part of the Scopes. This data was analyzed to gain insights into publication years, countries/regions, institutions, citations, and keywords. Co-occurrence network graphs were created using the VOSviewer Library, Publish or Perish, and CiteSpace tools on the online analysis platform. The analysis of AI-related antibiotic sensitivity research (2020–2025) highlights China’s guiding contribution, fluctuating magazine trends, disparities in institutional output, and a strong research focus on bacterial resistance, biofilms, and quorum sensing, with bibliometric analysis revealing the dominance of antibiotic resistance as a key topic and citation metrics showing rapidly evolving scientific discussions in microbiology and antimicrobial research. The study identified key focus areas and emerging trends in artificial intelligence for antibiotic resistance and the role of certain bacteria on the patient, suggesting that artificial intelligence will play an increasingly prominent role in antibiotic resistance moving forward.