Abstract
This research work introduces a solution approach for detecting infectious diseases in modern laboratory diagnostics. It combines an artificial intelligence (AI)-based data analysis by means of random forest methods with decision support based on intuitive information display and suitable planning functionality. The approach thereby bridges between AI-based automation and human decision making. It is realized as a prototypical diagnostic web service and demonstrated for the example of Covid-19 and Influenza A/B detection.
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This work was funded by the Fraunhofer Innovation Hub program Anti-Corona.
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Scherrer, A., Helmling, M., Singer, C., Riedel, S., Küfer, KH. (2022). Artificial Intelligence-Based Decision Support in Laboratory Diagnostics. In: Trautmann, N., Gnägi, M. (eds) Operations Research Proceedings 2021. OR 2021. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-08623-6_35
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DOI: https://doi.org/10.1007/978-3-031-08623-6_35
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