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Artificial Intelligence-Based Decision Support in Laboratory Diagnostics

In: Operations Research Proceedings 2021

Author

Listed:
  • Alexander Scherrer

    (Fraunhofer Institute for Industrial Mathematics (ITWM))

  • Michael Helmling

    (Fraunhofer Institute for Industrial Mathematics (ITWM))

  • Christian Singer

    (Fraunhofer Institute for Industrial Mathematics (ITWM))

  • Sinan Riedel

    (Fraunhofer Institute for Industrial Mathematics (ITWM))

  • Karl-Heinz Küfer

    (Fraunhofer Institute for Industrial Mathematics (ITWM))

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.

Suggested Citation

  • Alexander Scherrer & Michael Helmling & Christian Singer & Sinan Riedel & Karl-Heinz Küfer, 2022. "Artificial Intelligence-Based Decision Support in Laboratory Diagnostics," Lecture Notes in Operations Research, in: Norbert Trautmann & Mario Gnägi (ed.), Operations Research Proceedings 2021, pages 229-235, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-08623-6_35
    DOI: 10.1007/978-3-031-08623-6_35
    as

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