Machine-learning Assisted Dual-Primer High-Resolution Melt for Bacterial and Fungal Infections Detection

Bacterial and fungal infections pose significant health challenges due to their complex diagnosis and treatment requirements. Traditionally, culture-based methods have been the cornerstone for identifying these infections, yet they are notably slow, leading to treatment delays. In response, this study introduces a novel dual-primer digital PCR high-resolution melting (dual-primer HRM) platform for the rapid detection of bacterial and fungal polymicrobial infections. This approach enables the simultaneous amplification and identification of bacterial and fungal DNA through a single PCR assay. The integration of a nanoarray into this system allows for the digitization of pathogenic DNA molecules, facilitating the generation of digital melt curves directly from pathogenic DNA isolated in individual nanowells. Subsequently, precise pathogen identification is achieved by employing machine learning method for. This approach streamlines the diagnostic process, promising rapid and more precise identification of bacterial-fungal infections.