Emely Rosbach

Emely Rosbach

Researcher

TH Ingolstadt

I am a research assistant at the Technical University of Applied Sciences Ingolstadt, where I also received my Master’s degree in User Experience Design. My current research focuses on understanding how medical professionals interact with AI-based decision support systems in digital pathology and radiology. I am particularly interested in how human cognition, specifically cognitive biases, shapes human-machine collaboration in critical environments such as healthcare.

Publications

2026

2025

  • "When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology

    Emely Rosbach, Jonas Ammeling, Sebastian Krügel, Angelika Kießig, Alexis Fritz, Jonathan Ganz, Chloé Puget, Taryn Donovan, Andrea Klang, Maximilian C. Köller, Pompei Bolfa, Marco Tecilla, Daniela Denk, Matti Kiupel, Georgios Paraschou, Mun Keong Kok, Alexander F. H. Haake, Ronald R. De Krijger, Andreas F.-P. Sonnen, Tanit Kasantikul, Gerry M. Dorrestein, Rebecca C. Smedley, Nikolas Stathonikos, Matthias Uhl, Christof A. Bertram, Andreas Riener and Marc Aubreville

    Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems doi link

  • Automation Bias in AI-assisted Medical Decision-making under Time Pressure in Computational Pathology

    Emely Rosbach, Jonathan Ganz, Jonas Ammeling, Andreas Riener and Marc Aubreville

    Bildverarbeitung für die Medizin 2025 doi link

  • Is Self-supervision Enough?: Benchmarking Foundation Models Against End-to-end Training for Mitotic Figure Classification

    Jonathan Ganz, Jonas Ammeling, Emely Rosbach, Ludwig Lausser, Christof A. Bertram, Katharina Breininger and Marc Aubreville

    Bildverarbeitung für die Medizin 2025 doi link

2024

  • Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis

    Jonathan Ganz, Christian Marzahl, Jonas Ammeling, Emely Rosbach, Barbara Richter, Chloé Puget, Daniela Denk, Elena A. Demeter, Flaviu A. Tăbăran, Gabriel Wasinger, Karoline Lipnik, Marco Tecilla, Matthew J. Valentine, Michael J. Dark, Niklas Abele, Pompei Bolfa, Ramona Erber, Robert Klopfleisch, Sophie Merz, Taryn A. Donovan, Samir Jabari, Christof A. Bertram, Katharina Breininger and Marc Aubreville

    Scientific Reports doi link

  • Prediction of tumor board procedural recommendations using large language models

    Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Emely Rosbach, Thomas Gehrke, Agmal Scherzad, Stephan Hackenberg and Miguel Goncalves

    European Archives of Oto-Rhino-Laryngology doi link

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