The development of new antimicrobial agents is currently outpaced by the emergence of new antimicrobial resistance 1 (AMR). Moreover our application is suited for resource-limited settings, and therefore has the potential to significantly increase patients’ access to AST worldwide. The application’s performance showed that the automatic reading of antibiotic resistance testing is entirely feasible on a smartphone.
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The fully automatic measurement procedure of our application’s reading system achieves an overall agreement of 90% on susceptibility categorization against a hospital-standard automatic system and 98% against manual measurement (gold standard), with reduced inter-operator variability. An embedded expert system validates the coherence of the antibiogram data and provides interpreted results. The application captures images with the phone’s camera, and the user is guided throughout the analysis on the same device by a user-friendly graphical interface. We present an artificial intelligence (AI)-based, offline smartphone application for antibiogram analysis. Automatic reading systems address these issues, but are not always adapted or available to resource-limited settings.
While disk diffusion antibiotic susceptibility testing (AST, also called antibiogram) is broadly used to test for antibiotic resistance in bacterial infections, it faces strong criticism because of inter-operator variability and the complexity of interpretative reading. Antimicrobial resistance is a major global health threat and its development is promoted by antibiotic misuse.
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