Compliant motion of a multi-segmented inspection robot. - Clemens Birkenhofer; Michael Hoffmeister; Johann Marius Zöllner; Rüdiger Dillmann (IROS, 2005)

Enabling Fast Ramp-Up of Assembly Lines through Context-Mapping of Implicit Operator Knowledge and Machine-Derived Data. - Konstantin Konrad; Michael Hoffmeister; Matthias Zapp; Alexander Verl; Johannes Busse (IPAS, 2012)

Towards a Semantic Administrative Shell for Industry 4.0 Components. - Irlán Grangel-González; Lavdim Halilaj; Gökhan Coskun; Sören Auer; Diego Collarana; Michael Hoffmeister (ICSC, 2016)

The role of the Industry 4.0 asset administration shell and the digital twin during the life cycle of a plant. - Constantin Wagner; Julian Grothoff; Ulrich Epple; Rainer Drath; Somayeh Malakuti; Sten Grüner; Michael Hoffmeister; Patrick Zimmermann (ETFA, 2017)

The AutomationML Component Description in the context of the Asset Administration Shell. - Rainer Drath; Markus Rentschler; Michael Hoffmeister (ETFA, 2019)

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. - Narmin Ghaffari Laleh; Hannah Sophie Muti; Chiara Maria Lavinia Loeffler; Amelie Echle; Oliver Lester Saldanha; Faisal Mahmood 001; Ming Y. Lu; Christian Trautwein; Rupert Langer; Bastian Dislich; Roman David Bülow; Heike Irmgard Grabsch; et al. (Medical Image Anal., 2022)

Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474. - Narmin Ghaffari Laleh; Hannah Sophie Muti; Chiara Maria Lavinia Loeffler; Amelie Echle; Oliver Lester Saldanha; Faisal Mahmood 001; Ming Y. Lu; Christian Trautwein; Rupert Langer; Bastian Dislich; Roman David Bülow; Heike Irmgard Grabsch; et al. (Medical Image Anal., 2022)

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study. - Sophia J. Wagner; Daniel Reisenbüchler; Nicholas P. West; Jan Moritz Niehues; Gregory Patrick Veldhuizen; Philip Quirke; Heike Irmgard Grabsch; Piet A. van den Brandt; Gordon G. A. Hutchins; Susan D. Richman; Tanwei Yuan; Rupert Langer; et al. (CoRR, 2023)

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides. - Omar S. M. El Nahhas; Chiara Maria Lavinia Loeffler; Zunamys I. Carrero; Marko van Treeck; Fiona R. Kolbinger; Katherine Jane Hewitt; Hannah Sophie Muti; Mara Graziani; Qinghe Zeng; Julien Calderaro; Nadina Ortiz-Brüchle; Tanwei Yuan; et al. (CoRR, 2023)

Machine learning in the identification of prognostic DNA methylation biomarkers among patients with cancer: A systematic review of epigenome-wide studies. - Tanwei Yuan; Dominic Edelmann; Ziwen Fan; Elizabeth Alwers; Jakob Nikolas Kather; Hermann Brenner; Michael Hoffmeister (Artif. Intell. Medicine, 2023)

Benchmarking foundation models as feature extractors for weakly-supervised computational pathology. - Peter Neidlinger; Omar S. M. El Nahhas; Hannah Sophie Muti; Tim Lenz; Michael Hoffmeister; Hermann Brenner; Marko van Treeck; Rupert Langer; Bastian Dislich; Hans-Michael Behrens; Christoph Röcken; Sebastian Foersch; et al. (CoRR, 2024)

Encrypted federated learning for secure decentralized collaboration in cancer image analysis. - Daniel Truhn; Soroosh Tayebi Arasteh; Oliver Lester Saldanha; Gustav Müller-Franzes; Firas Khader; Philip Quirke; Nicholas P. West; Richard Gray 005; Gordon G. A. Hutchins; Jacqueline A. James; Maurice B. Loughrey; Manuel Salto-Tellez; et al. (Medical Image Anal., 2024)

A deep learning framework for efficient pathology image analysis. - Peter Neidlinger; Tim Lenz; Sebastian Foersch; Chiara Maria Lavinia Loeffler; Jan Clusmann; Marco Gustav; Lawrence A. Shaktah; Rupert Langer; Bastian Dislich; Lisa A. Boardman; Amy J. French; Ellen L. Goode; et al. (CoRR, 2025)