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  • Healthcare: Automated Identification of Microorganism Images

    Nasreddine Menacer, a faculty member and head of online programs at aivancity, supervised a project carried out as part of the school’s AI Clinic, in collaboration with a company specializing in image analysis for microbiology laboratories. The project involved developing an AI model to accurately segment microbes and bacteria in microbiological images. This solution improves the identification and counting of microorganisms, which optimizes research methods while reducing repetitive manual tasks. Technically, the AI relies on images annotated by experts, which are then used to train an FCN-type neural network model. The model has shown satisfactory results, although risks related to the quality of annotations and the diversity of training data remain. This project has improved the accuracy of microbiological analyses, reducing analysis time and thereby freeing up time for high-value-added tasks. It has also helped strengthen the company’s business performance.

    Nasreddine Menacer, a faculty member and head of online programs at aivancity, supervised a project carried out as part of the school’s AI Clinic, in collaboration with a company specializing in image analysis for microbiology laboratories.

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