HIS-based electronic documentation can significantly reduce the time from biopsy to final report for prostate tumours and supports quality management as well as clinical research. - Bernhard Breil; Axel Semjonow; Martin Dugas (BMC Medical Informatics Decis. Mak., 2009)

Clinical map document based on XML (cMDX): document architecture with mapping feature for reporting and analysing prostate cancer in radical prostatectomy specimens. - Okyaz Eminaga; Reemt Hinkelammert; Axel Semjonow; Joerg Neumann; Mahmoud Abbas; Thomas Koepke; Olaf Bettendorf; Elke Eltze; Martin Dugas (BMC Medical Informatics Decis. Mak., 2010)

HIS-based Kaplan-Meier plots - a single source approach for documenting and reusing routine survival information. - Bernhard Breil; Axel Semjonow; Carsten Müller-Tidow; Fleur Fritz; Martin Dugas (BMC Medical Informatics Decis. Mak., 2011)

CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer. - Okyaz Eminaga; Mahmoud Abbas; Reemt Hinkelammert; Ulf Titze; Olaf Bettendorf; Elke Eltze; Enver Özgür; Axel Semjonow (BMC Medical Informatics Decis. Mak., 2012)

Linkage of Data from Diverse Data Sources (LDS): A Data Combination Model Provides Clinical Data of Corresponding Specimens in Biobanking Information System. - Okyaz Eminaga; Enver Özgür; Axel Semjonow; Jan Herden; Ilgar Akbarov; Ali Tok; Udo Engelmann; Sebastian Wille (J. Medical Syst., 2013)

The need for harmonized structured documentation and chances of secondary use - Results of a systematic analysis with automated form comparison for prostate and breast cancer. - Rainer Krumm; Axel Semjonow; Joke Tio; Heike Duhme; Thomas Bürkle; Jörg Haier; Martin Dugas; Bernhard Breil (J. Biomed. Informatics, 2014)

Analysis of topographical distribution of prostate cancer and related pathological findings in prostatectomy specimens using cMDX document architecture. - Okyaz Eminaga; Axel Semjonow; Elke Eltze; Olaf Bettendorf; Anne Schultheis; Ute Warnecke-Eberz; Ilgar Akbarov; Sebastian Wille; Udo Engelmann (J. Biomed. Informatics, 2016)

Deep Learning for Prostate Pathology. - Okyaz Eminaga; Yuri Tolkach; Christian Kunder; Mahmoud Abbas; Ryan Han; Rosalie Nolley; Axel Semjonow; Martin Boegemann; Sebastian Huss; Andreas M. Loening; Robert B. West; Geoffrey A. Sonn; et al. (CoRR, 2019)

Biologic and Prognostic Feature Scores from Whole-Slide Histology Images Using Deep Learning. - Okyaz Eminaga; Mahmoud Abbas; Yuri Tolkach; Rosalie Nolley; Christian Kunder; Axel Semjonow; Martin Boegemann; Andreas M. Loening; James D. Brooks; Daniel L. Rubin (CoRR, 2019)

Combination possibility and deep learning model as clinical decision-aided approach for prostate cancer. - Okyaz Eminaga; Omran Al-Hamad; Martin Boegemann; Bernhard Breil; Axel Semjonow (Health Informatics J., 2020)

Critical Evaluation of Artificial Intelligence as Digital Twin of Pathologist for Prostate Cancer Pathology. - Okyaz Eminaga; Mahmoud Abbas; Christian Kunder; Yuri Tolkach; Ryan Han; James D. Brooks; Rosalie Nolley; Axel Semjonow; Martin Boegemann; Robert B. West; Jin Long; Richard E. Fan; et al. (CoRR, 2023)