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André Schulze

Showing results (1-10 of 9) with videos related to

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Chirurgie (Heidelberg, Germany)|March 5, 2024
[The digital operating room : Chances and risks of artificial intelligence]Ann Wierick, André Schulze, Sebastian Bodenstedt, et al.
Zentralblatt Fur Chirurgie|October 2, 2025
André Schulze, Johanna Brandenburg, Rayan Younis, et al.
Micromachines|May 12, 2019
Self-Learning Microfluidic Platform for Single-Cell Imaging and Classification in FlowIordania Constantinou, Michael Jendrusch, Théo Aspert, et al.
International Journal of Computer Assisted Radiology and Surgery|June 15, 2026
Stream-based active learning for surgical AIGregor Just, Alexander C Jenke, Antonia Kraneis, et al.
Journal of Cancer Research and Clinical Oncology|May 26, 2022
Machine learning for optimized individual survival prediction in resectable upper gastrointestinal cancerJin-On Jung, Nerma Crnovrsanin, Naita Maren Wirsik, et al.
International Journal of Surgery (London, England)|March 27, 2025
AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery - an experimental studyFiona R Kolbinger, Nithya Bhasker, Felix Schön, et al.
European Journal of Surgical Oncology : the Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology|November 15, 2025
Surgical workflow analysis for Surgomics and context-aware assistance in robot-assisted minimally invasive esophagectomy (RAMIE): a retrospective, single-arm, multicenter annotation and machine learning studyJohanna M Brandenburg, André Schulze, Alexander C Jenke, et al.
Surgical Endoscopy|September 28, 2022
Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal dataMartin Wagner, Johanna M Brandenburg, Sebastian Bodenstedt, et al.
Surgical Endoscopy|October 13, 2023
Active learning for extracting surgomic features in robot-assisted minimally invasive esophagectomy: a prospective annotation studyJohanna M Brandenburg, Alexander C Jenke, Antonia Stern, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Chirurgie (Heidelberg, Germany)|March 5, 2024
[The digital operating room : Chances and risks of artificial intelligence]Ann Wierick, André Schulze, Sebastian Bodenstedt, et al.
Zentralblatt Fur Chirurgie|October 2, 2025
André Schulze, Johanna Brandenburg, Rayan Younis, et al.
Micromachines|May 12, 2019
Self-Learning Microfluidic Platform for Single-Cell Imaging and Classification in FlowIordania Constantinou, Michael Jendrusch, Théo Aspert, et al.
International Journal of Computer Assisted Radiology and Surgery|June 15, 2026
Stream-based active learning for surgical AIGregor Just, Alexander C Jenke, Antonia Kraneis, et al.
Journal of Cancer Research and Clinical Oncology|May 26, 2022
Machine learning for optimized individual survival prediction in resectable upper gastrointestinal cancerJin-On Jung, Nerma Crnovrsanin, Naita Maren Wirsik, et al.
International Journal of Surgery (London, England)|March 27, 2025
AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery - an experimental studyFiona R Kolbinger, Nithya Bhasker, Felix Schön, et al.
European Journal of Surgical Oncology : the Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology|November 15, 2025
Surgical workflow analysis for Surgomics and context-aware assistance in robot-assisted minimally invasive esophagectomy (RAMIE): a retrospective, single-arm, multicenter annotation and machine learning studyJohanna M Brandenburg, André Schulze, Alexander C Jenke, et al.
Surgical Endoscopy|September 28, 2022
Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal dataMartin Wagner, Johanna M Brandenburg, Sebastian Bodenstedt, et al.
Surgical Endoscopy|October 13, 2023
Active learning for extracting surgomic features in robot-assisted minimally invasive esophagectomy: a prospective annotation studyJohanna M Brandenburg, Alexander C Jenke, Antonia Stern, et al.
Pageof 1