Ultrasensitive Staphylococcus aureus Detection via Machine Learning-Optimized Bacterial-Imprinted Photoelectrochemical Biosensor with Active/Passive Dual-Mode Validation

CFU/mL. The preparation and detection of sensors were analyzed and predicted by using molecular docking and machine learning. This work significantly mitigates the impact of interference factors in the conventional mode, providing numerous benefits, including convenience and speed, efficiency, and accuracy, and holds a highly promising method for microorganism detection in food and environmental domains.