ARTIFICIAL INTELLIGENCE IN HOSPITAL INFECTION CONTROL

Hospital-acquired infections (HAIs) pose a significant threat to patient safety and public health worldwide. The emergence of antimicrobial resistance and the COVID-19 pandemic have underscored the need for innovative solutions to enhance infection control (IC) practices. Artificial intelligence (AI) has emerged as a game-changer in IC, offering a powerful tool to automate manual tasks, provide real-time insights, and personalize IC strategies.The integration of AI in IPC has the potential to enhance patient safety, reduce HAIs, and improve overall healthcare quality. This review explores the applications of AI in IC, including predictive analytics, automated surveillance, clinical decision support systems, and environmental cleaning and disinfection and personalized medicine. AI-powered systems can analyze large datasets, identify patterns, and provide real-time insights, enabling healthcare professionals to predict, detect, and prevent hospital-acquired infections (HAIs) more effectively. The integration of AI in IPC has the potential to enhance patient safety, reduce HAIs, and improve overall healthcare quality. However, challenges and limitations, such as data quality, algorithmic bias, and clinical adoption, must be addressed to ensure the effective and safe implementation of AI-powered IPC systems. This review highlights the transformative potential of AI in IPC and emphasizes the need for further research and collaboration to harness the full potential of AI in improving patient outcomes and healthcare quality. This comprehensive review also explores the applications of AI in IPC, including intelligent waste management, antimicrobial resistance detection, and precision prescribing. AI-powered systems can analyze vast amounts of data, identify patterns, and provide real-time insights, enabling healthcare professionals to predict, detect, and prevent hospital-acquired infections (HAIs) more effectively. This review highlights the transformative potential of AI in IPC and emphasizes the need for further research and collaboration to harness the full potential of AI in improving patient outcomes and healthcare quality. The integration of artificial intelligence (AI) in infection prevention and control (IPC) has revolutionized the field, offering unparalleled opportunities for enhancing patient outcomes, improving IPC, and streamlining clinical workflows. This comprehensive review explores the applications, benefits, and challenges of AI in IPC. Despite the potential benefits, several research gaps exist, including the need for standardized methodologies, validation processes, and addressing ethical and regulatory considerations. This review highlights the transformative potential of emphasizes the need for collaboration among healthcare professionals, researchers, and policymakers to ensure the effective development, implementation, and regulation of AI-powered IPC systems. By leveraging AI, healthcare organizations can improve patient outcomes, reduce HAIs, and enhance the overall quality of care.