The rapid and accurate identification of bacterial pathogens is crucial for public health, clinical diagnostics, and environmental monitoring. However, current methods, including culture-based techniques and untargeted metagenomics, are often slow, labor-intensive, or lack the sensitivity to detect low-abundance pathogens within complex samples. To address these limitations, we developed an integrated platform that combines targeted nanopore sequencing using a tailored artificial intelligence (AI) model for comprehensive pathogen assessment. The long-read capability of Oxford Nanopore Technologies enables real-time sequencing and precise enrichment of pathogens of interests. The electrical signals are used directly to decide if the sequenced pathogens are from the selected species or from different sources. We validated our platform on a diverse set of samples, demonstrating concordance with standard diagnostics while significantly reducing turnaround time. This AI-empowered, targeted nanopore sequencing platform represents a significant advancement for high-resolution, real-time surveillance of bacterial pathogens, with profound implications for precision medicine, outbreak investigation, and One Health monitoring.

AI model,targeted nanopore sequencing,,pathogen assessment,one health monitoring