Klinische Epidemiologie beidseitiger Mammakarziome. - Hermann Brenner; B. Engelsmann; Christa Stegmaier; Hartwig Ziegler (GMDS, 1994)

Ein neues Verfahren zur Korrektur des Schätzers für das relative Risiko bei Fehlklassifikation des Erkrankungsstatus. - Hermann Brenner; Olaf Gefeller (GMDS, 1994)

Einfache Fallzählung oder anspruchsvolle Biometrie? - Hermann Brenner (GMDS, 1996)

A computer program to estimate power and relative efficiency to assess multiplicative interactions in flexibly matched case-control studies. - T. Stürmer; Olaf Gefeller; Hermann Brenner (Comput. Methods Programs Biomed., 2004)

Model based period analysis of absolute and relative survival with R: Data preparation, model fitting and derivation of survival estimates. - Bernd Holleczek; Hermann Brenner (Comput. Methods Programs Biomed., 2013)

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns. - Hui-Yi Lin; Dung-Tsa Chen; Po-Yu Huang; Yung-Hsin Liu; Augusto Ochoa; Jovanny Zabaleta; Donald Mercante; Zhide Fang; Thomas A. Sellers; Julio M. Pow-Sang; Chia-Ho Cheng; Rosalind A. Eeles; et al. (Bioinform., 2017)

AA9int: SNP interaction pattern search using non-hierarchical additive model set. - Hui-Yi Lin; Po-Yu Huang; Dung-Tsa Chen; Heng-Yuan Tung; Thomas A. Sellers; Julio M. Pow-Sang; Rosalind A. Eeles; Doug Easton; Zsofia Kote-Jarai; Ali Amin Al Olama; Sara Benlloch; Kenneth Muir; et al. (Bioinform., 2018)

Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data. - Heike Deutelmoser; Dominique Scherer; Hermann Brenner; Melanie Waldenberger; Karsten Suhre; Gabi Kastenmüller; Justo Lorenzo Bermejo (Briefings Bioinform., 2021)

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study. - Emma Nichols; Foad Abd-Allah; Amir Abdoli; Ahmed Abualhasan; Eman Abu-Gharbieh; Ashkan Afshin; Rufus Akinyemi; Fahad Mashhour Alanezi; Vahid Alipour; Amir Almasi-Hashiani; Jalal Arabloo; Amir Ashraf-Ganjouei; et al. (BMC Medical Informatics Decis. Mak., 2021)

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)