Artificial Intelligence in Infectious Diseases and Clinical Microbiology: Current and Future Directions

Abstract

Artificial intelligence (AI) is increasingly applied in infectious diseases and clinical microbiology, encompassing diagnostics, treatment, infection control, and antimicrobial stewardship, with transformative potential across many aspects of daily clinical practice. The integration of imaging modalities, molecular and microbiological tests, and host-response–based classifiers with AI algorithms enhances diagnostic accuracy and facilitates clinical decision-making. In the context of treatment, AI supports patient management by enabling personalized antibiotic selection, optimizing treatment duration, predicting resistance, and providing clinical decision support. For infection control, AI-driven applications such as early outbreak detection, real-time surveillance, hand hygiene monitoring, and environmental disinfection are becoming more prevalent. Despite these advancements, challenges persist, including data heterogeneity, limited algorithmic explainability, ethical and legal considerations, and concerns regarding patient privacy. With multidisciplinary collaboration, high-quality data generation, and robust regulatory frameworks, AI systems are anticipated to become reliable and effective decision-support tools in infectious diseases practice.

Ähnliche Arbeiten