Ponentes: Marco Pascucci (Investigador Postdoctoral, Laboratoire de Mathématiques et Modélisation d’Évry), https://mpascucci.github.io.

Lugar: online (https://bit.ly/salaDMC).

Hora: miércoles 21 de abril, 10:00

Resumen: Antimicrobial resistance is a major global health threat and its development is promoted by antibiotic misuse. 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. Automatic reading systems address these issues, but are not always adapted or available to resource-limited settings and come with high costs. We present a smartphone application for antibiogram analysis. 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. Image processing and result analysis are entirely done offline on a smartphone. Our application is suited for resource-limited settings, it aims to lower the entry effort for performing AST testing and therefore increase patients’ access to AST worldwide.

Nota 01: la aplicación móvil presentada fue distinguida con el Google AI Impact Challenge 2019. También ha sido presentada en un reciente número de la revista Nature Communications.

Nota 02: si quieres acceder a la aplicación desarrollada (todavía en fase de pruebas) lo puedes hacer rellenando el siguiente formulario: https://form.typeform.com/to/qEGVBzbu.