The Role of Artificial Intelligence in Enhancing Infection Control in Hospitals: A Systematic Review
Abstract
Hospital-acquired infections represent a critical global healthcare challenge, affecting 7–10% of hospitalized patients worldwide with 1.4 million annual deaths. This systematic review examines the transformative potential of artificial intelligence in infection control through predictive analytics, real-time surveillance, and antimicrobial stewardship. Analyzing 50 peer-reviewed studies, we demonstrate the effectiveness of AI tools in reducing infection rates by 35% and improving antibiotic utilization by 90%. We identify key implementation barriers, including data integration challenges, algorithmic bias, and ethical concerns. By synthesizing real-world case studies and proposing a three-phase implementation model, this review bridges the gap between technological capabilities and hospital infection control policies, offering practical recommendations and outlining a roadmap for future integration.
First Page
250
Last Page
255
Recommended Citation
Alquthami, Khalid M.; Alahdal, Ali M.; Serdar, Sadiq A.; Kheyami, Mazin M.; Alwadani, Mohammed A.; Barashi, Razaz A.; Alkhozaee, Mohammad M.; and Jawa, Basem A.
(2025)
"The Role of Artificial Intelligence in Enhancing Infection Control in Hospitals: A Systematic Review,"
Journal of King Abdulaziz University: Medical Sciences: Vol. 32:
Iss.
2, Article 18.
DOI: https://doi.org/10.64064/1658-4279.1027
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