Rapid SERS identification of methicillin-susceptible and methicillin-resistant <i>Staphylococcus aureus via</i> aptamer recognition and deep learning
Shu Wang, Hao Dong, Wanzhu Shen, Yong Yang, Zhigang Li, Yong Liu, Chongwen Wang, Bing Gu, Long Zhang
Abstract
), comprising 30 strains of MSSA and 30 strains of MRSA were used to build the CNN classification model. The developed method exhibited 100% identification accuracy for MSSA and MRSA, and is thus a promising tool for the rapid detection of drug-sensitive and drug-resistant bacterial strains.
Topics & Concepts
Staphylococcus aureusMethicillin-resistant Staphylococcus aureusMicrobiologyAptamerIdentification (biology)Convolutional neural networkArtificial intelligenceBiologyComputer scienceBacteriaMolecular biologyGeneticsBotanyBiosensors and Analytical DetectionBacterial Identification and Susceptibility TestingSpectroscopy Techniques in Biomedical and Chemical Research