Prof. Dr.-Ing. Marc Aubreville

2026

• Stuck on Suggestions: Automation Bias, the Anchoring Effect, and the Factors That Shape Them in Computational Pathology

  Rosbach, E., Ammeling, J., Ganz, J., Bertram, C. A., Conrad, T., Riener, A., & Aubreville, M. (2026). Stuck on Suggestions: Automation Bias, the Anchoring Effect, and the Factors That Shape Them in Computational Pathology. Machine Learning for Biomedical Imaging, 3, 126–147. http://doi.org/https://doi.org/10.59275/j.melba.2026-87b1 (Original work published 2026)

• Feasibility of confocal laser endomicroscopy as an optical biopsy method for SCC on the auricle : an exploratory study

  Müller-Diesing, F., Sievert, M., Panuganti, B., Aubreville, M., Porsche, N., Hackenberg, S., … Goncalves, M. (2026). Feasibility of confocal laser endomicroscopy as an optical biopsy method for SCC on the auricle : an exploratory study. Oral and Maxillofacial Surgery, 30(1), 21+. http://doi.org/10.1007/s10006-026-01506-y

• Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation

  Banerjee, S. ", Weiss, V., Donovan, T. A., Fick, R., Conrad, T., Ammeling, J., … Bertram, C. A. (2026). Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation. Machine Learning for Biomedical Imaging, 3, 115–125. http://doi.org/https://doi.org/10.59275/j.melba.2026-6c1g