Thesis Title: Development of electrochemical sensors for bloodstream infection diagnostic
Moreover, these signals could be exploited by machine learning in order to identify the detected pathogen, without manipulation or chemical reagent. This technology would thus allow to valorize the transport time and to automate the first steps of identification to generate a relevant diagnosis in the shortest time. The last works carried out during this thesis allowed to study the biological and chemical phenomena involved during the detection and identification. These results open the way to numerous applications and research themes, particularly in the field of bacterial biofilms.
Key Words: Electrochemical sensors, biological diagnostic, blood culture, in vitro diagnostic, machine learning, label-free identification
Doctoral School: ED I-MEP² - Engineering - Materials, Mechanical, Environment, Energetics, Processes, Production
Research laboratory: Laboratoire d'électronique et de technologie de l'information (CEA- Leti)
Thesis supervision: Pascal MAILLEY, Pierre MARCOUX and Maxime GOUGIS
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