An artificial neural network model for the recognition of Escherichia coli O157:H7 restriction patterns was designed. In the training phase, images of two classes of E. coli isolates (O157:H7 and non-O157:H7) were digitized and transmitted to the neural network. The system was then tested for recognition of images not included in the training set, Promising results were achieved with the designed network configuration, providing a basis for further study. This application of a new generation of computational technology serves as an example of its usefulness in microbiology.
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UNIV BRITISH COLUMBIA, BRITISH COLUMBIAS CHILDRENS HOSP, VANCOUVER V6H 3R4, BC, CANADAUNIV BRITISH COLUMBIA, BRITISH COLUMBIAS CHILDRENS HOSP, VANCOUVER V6H 3R4, BC, CANADA
CIMOLAI, N
ANDERSON, JD
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UNIV BRITISH COLUMBIA, BRITISH COLUMBIAS CHILDRENS HOSP, VANCOUVER V6H 3R4, BC, CANADAUNIV BRITISH COLUMBIA, BRITISH COLUMBIAS CHILDRENS HOSP, VANCOUVER V6H 3R4, BC, CANADA
ANDERSON, JD
MORRISON, BJ
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UNIV BRITISH COLUMBIA, BRITISH COLUMBIAS CHILDRENS HOSP, VANCOUVER V6H 3R4, BC, CANADAUNIV BRITISH COLUMBIA, BRITISH COLUMBIAS CHILDRENS HOSP, VANCOUVER V6H 3R4, BC, CANADA