Developing a Region-Wide Machine-Learning–Empowered Platform for Actionable Genomic Epidemiology of Antimicrobial-Resistant Bacterial Clones

Nosocomial infections, often caused by Antibiotic-resistant bacteria, pose a heavy healthcare and economic burden worldwide. We propose an actionable genomic epidemiology platform across 3 hospitals in Lombardy to monitor antimicrobial-resistant Klebsiella pneumoniae lineages. The platform will combine patient data and genomic analysis to map transmission and predict outbreaks. Machine learning will help identify high-risk patients and detect known clones from MALDI-TOF Mass Spectrometry data, enabling fast and scalable surveillance. The platform impact and cost-effectiveness will be evaluated