A computer program utilizing a Baysean mathematical model was developed to identify bacteria solely on the basis of their antibiotic sensitivities. The model contains probability data on the antibiotic sensitivity patterns for 31 species of bacteria, which account for over 99% of all isolates submitted for testing. During a 4 mth test period, antibiotic sensitivity data on 1,000 clinical isolates were processed by the program. The identification achieved by using the model was the same as that of the laboratory for over 86% of the isolates.
ASJC Scopus subject areas
- Applied Microbiology and Biotechnology