Akademik Veri Yönetim Sistemi
Klimik Dergisi, cilt.39, sa.1, 2026 (ESCI, Scopus, TRDizin)
Artificial intelligence (AI) is increasingly applied in infectious diseases and clinical microbiology, encompassing diag-nostics, 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 algo-rithmic 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.