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Maurice Moelleken

Showing results (21-30 of 32) with videos related to

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International Wound Journal|August 1, 2023
Predilection sites of pyoderma gangrenosum: Retrospective study of 170 clearly diagnosed patientsMaurice Moelleken, Cornelia Erfurt-Berge, Moritz Ronicke, et al.
Studies in Health Technology and Informatics|January 22, 2022
Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound MacerationJens Hüsers, Guido Hafer, Jan Heggemann, et al.
Studies in Health Technology and Informatics|September 5, 2024
Automation Bias in AI-Decision Support: Results from an Empirical StudyFlorian Kücking, Ursula Hübner, Mareike Przysucha, et al.
Studies in Health Technology and Informatics|September 12, 2023
Design and Implementation of an ETL-Process to Transfer Wound-Related Data into a Standardized Common Data ModelMareike Przysucha, Jens Hüsers, Daniil Liberman, et al.
Scientific Reports|April 16, 2024
Comparison of visual diagnostic accuracy of dermatologists practicing in Germany in patients with light skin and skin of colorFrederik Krefting, Maurice Moelleken, Stefanie Hölsken, et al.
International Wound Journal|April 16, 2025
Chronic Wounds and Employment: Assessing Occupation-Related Burden of Patients With Chronic Wounds-Results of a Pilot StudyDorothee Ann-Kathrin Busch, Nicole Methner, Delara Azodanlou, et al.
American Journal of Clinical Dermatology|November 14, 2024
Intravenous Immunoglobulin Therapy for Pyoderma Gangrenosum: A Multicenter Retrospective Analysis in 81 PatientsMoritz Ronicke, Lukas Sollfrank, Martin V Vitus, et al.
Studies in Health Technology and Informatics|July 1, 2022
Automatic Wound Type Classification with Convolutional Neural NetworksLeila Malihi, Jens Hüsers, Mats L Richter, et al.
BMJ Health & Care Informatics|October 10, 2025
Machine learning model to classify chronic leg wounds and identify pyoderma gangrenosumDorothee A Busch, Mats L Richter, Jens Hüsers, et al.
Studies in Health Technology and Informatics|May 19, 2023
Can Synthetic Images Improve CNN Performance in Wound Image Classification?Leila Malihi, Ursula Hübner, Mats L Richter, et al.
Pageof 4

Showing results (21-30 of 32) with videos related to

Sort By:
Pageof 4
International Wound Journal|August 1, 2023
Predilection sites of pyoderma gangrenosum: Retrospective study of 170 clearly diagnosed patientsMaurice Moelleken, Cornelia Erfurt-Berge, Moritz Ronicke, et al.
Studies in Health Technology and Informatics|January 22, 2022
Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound MacerationJens Hüsers, Guido Hafer, Jan Heggemann, et al.
Studies in Health Technology and Informatics|September 5, 2024
Automation Bias in AI-Decision Support: Results from an Empirical StudyFlorian Kücking, Ursula Hübner, Mareike Przysucha, et al.
Studies in Health Technology and Informatics|September 12, 2023
Design and Implementation of an ETL-Process to Transfer Wound-Related Data into a Standardized Common Data ModelMareike Przysucha, Jens Hüsers, Daniil Liberman, et al.
Scientific Reports|April 16, 2024
Comparison of visual diagnostic accuracy of dermatologists practicing in Germany in patients with light skin and skin of colorFrederik Krefting, Maurice Moelleken, Stefanie Hölsken, et al.
International Wound Journal|April 16, 2025
Chronic Wounds and Employment: Assessing Occupation-Related Burden of Patients With Chronic Wounds-Results of a Pilot StudyDorothee Ann-Kathrin Busch, Nicole Methner, Delara Azodanlou, et al.
American Journal of Clinical Dermatology|November 14, 2024
Intravenous Immunoglobulin Therapy for Pyoderma Gangrenosum: A Multicenter Retrospective Analysis in 81 PatientsMoritz Ronicke, Lukas Sollfrank, Martin V Vitus, et al.
Studies in Health Technology and Informatics|July 1, 2022
Automatic Wound Type Classification with Convolutional Neural NetworksLeila Malihi, Jens Hüsers, Mats L Richter, et al.
BMJ Health & Care Informatics|October 10, 2025
Machine learning model to classify chronic leg wounds and identify pyoderma gangrenosumDorothee A Busch, Mats L Richter, Jens Hüsers, et al.
Studies in Health Technology and Informatics|May 19, 2023
Can Synthetic Images Improve CNN Performance in Wound Image Classification?Leila Malihi, Ursula Hübner, Mats L Richter, et al.
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