Restricted Versus Unrestricted Search Space: Experience from Mining a Large Japanese Database. - Hendrik Nienhoff; Ursula Hübner; Andreas Frey; Mareike Przysucha; Michio Kimura (MedInfo, 2015)

The Benefits of a Formative Evaluation for Developing a Highly Innovative Software: The Case of the handoverEHR. - Mareike Przysucha; Daniel Flemming; Ursula Hübner (MIE, 2016)

Cognitive Performance of Users Is Affected by Electronic Handovers Depending on Role, Task and Human Factors. - Mareike Przysucha; Daniel Flemming; Georg Schulte; Ursula Hübner (GMDS, 2017)

Patient Handovers - Cognitively Demanding: Does the Handover EHR Meet This Challenge? - Ursula Hübner; Mareike Przysucha (MedInfo, 2017)

Requirements for Collaborative Decision Support Systems in Wound Care: No Information Continuity Without Management Continuity. - Mareike Przysucha; Stefan Vogel 001; Jens Hüsers; Stefanie Wache; Björn Sellemann; Ursula Hübner (GMDS, 2018)

Implementation and Analysis of Two Knowledge Base Approaches for the Treatment of Chronic Wounds. - Stefan Vogel 001; Jendrik Richter; Stefanie Wache; Kerstin Pischek-Koch; Simon Auchter; Sebastian Zebbities; Karen Güttler; Ursula Hübner; Mareike Przysucha; Jens Hüsers; Björn Sellemann (MIE, 2020)

Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound Maceration. - Jens Hüsers; Guido Hafer; Jan Heggemann; Stefan Wiemeyer; Mareike Przysucha; Joachim Dissemond; Maurice Moelleken; Cornelia Erfurt-Berge; Ursula Hübner (ICIMTH, 2021)

Evaluation of a Clinical Decision Support System in the Domain of Chronic Wound Management. - Stefan Vogel 001; Jendrik Richter; Stefanie Wache; Kerstin Pischek-Koch; Simone Auchter; Sebastian Zebbities; Karen Güttler; Ursula Hübner; Mareike Przysucha; Jens Hüsers; Björn Sellemann (MIE, 2021)

What Went Wrong in eMedCare? Formative Evaluation of an IT Project in Primary Care in Two Rural Districts. - Mareike Przysucha; Lara Peters; Andreas Büscher; Martin Schnellhammer; Ursula Hübner (GMDS, 2022)

Automatic Wound Type Classification with Convolutional Neural Networks. - Leila Malihi; Jens Hüsers; Mats L. Richter; Maurice Moelleken; Mareike Przysucha; Dorothee Busch; Jan Heggemann; Guido Hafer; Stefan Wiemeyer; Gunther Heidemann; Joachim Dissemond; Cornelia Erfurt-Berge; et al. (ICIMTH, 2022)

An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers. - Jens Hüsers; Maurice Moelleken; Mats L. Richter; Mareike Przysucha; Leila Malihi; Dorothee Busch; Nina-Alexandra Götz; Jan Heggemann; Guido Hafer; Stefan Wiemeyer; Birgit Babitsch; Gunther Heidemann; et al. (MIE, 2022)

Adoption and Determinants of Assistive Technologies in the Real World: Results from the VdK Study. - Ursula Hübner; Ivanna Yalymova; Mareike Przysucha; Andreas Büscher (GMDS, 2023)

Design and Implementation of an ETL-Process to Transfer Wound-Related Data into a Standardized Common Data Model. - Mareike Przysucha; Jens Hüsers; Daniil Liberman; Oliver Kersten; Aphrodite Schlüter; Sebastian Fraas; Dorothee Busch; Maurice Moelleken; Cornelia Erfurt-Berge; Joachim Dissemond; Ursula Hübner (GMDS, 2023)

Can Synthetic Images Improve CNN Performance in Wound Image Classification? - Leila Malihi; Ursula Hübner; Mats L. Richter; Maurice Moelleken; Mareike Przysucha; Dorothee Busch; Jan Heggemann; Guido Hafer; Stefan Wiemeyer; Gunther Heidemann; Joachim Dissemond; Cornelia Erfurt-Berge; et al. (MIE, 2023)

Automation Bias in AI-Decision Support: Results from an Empirical Study. - Ursula Hübner; Mareike Przysucha; Niels Hannemann; Jan-Oliver Kutza; Maurice Moelleken; Cornelia Erfurt-Berge; Joachim Dissemond; Birgit Babitsch; Dorothee Busch (GMDS, 2024)

Automatic Classification of Wound Images Showing Healing Complications: Towards an Optimised Approach for Detecting Maceration. - Leila Malihi; Cornelia Erfurt-Berge; Gunther Heidemann; Mareike Przysucha; Dorothee Busch; Ursula Hübner (GMDS, 2024)