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Artificial Intelligence in Medicine
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November 18, 2025
Enhancing transformer-based architectures with geometric deep learning for colonoscopic polyp size classification using transfer learning
Adrian Krenzer, Stefan Heil, Frank Puppe
Studies in Health Technology and Informatics
|
May 27, 2021
Semi-Automated Machine Learning Video Annotation for Gastroenterologists
Adrian Krenzer, Kevin Makowski, Amar Hekalo, et al.
BMC Medical Imaging
|
April 20, 2023
Automated classification of polyps using deep learning architectures and few-shot learning
Adrian Krenzer, Stefan Heil, Daniel Fitting, et al.
Gastrointestinal Endoscopy
|
December 20, 2021
New concept for colonoscopy including side optics and artificial intelligence
Joel Troya, Adrian Krenzer, Krzysztof Flisikowski, et al.
Biomedical Engineering Online
|
May 25, 2022
Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists
Adrian Krenzer, Kevin Makowski, Amar Hekalo, et al.
United European Gastroenterology Journal
|
May 5, 2022
Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions
Markus Brand, Joel Troya, Adrian Krenzer, et al.
Digestion
|
June 29, 2022
Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies
Markus Brand, Joel Troya, Adrian Krenzer, et al.
Journal of Imaging
|
February 24, 2023
A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks
Adrian Krenzer, Michael Banck, Kevin Makowski, et al.
Endoscopy
|
August 2, 2023
Direct comparison of multiple computer-aided polyp detection systems
Joel Troya, Boban Sudarevic, Adrian Krenzer, et al.
International Journal of Colorectal Disease
|
May 11, 2022
Pilot study of a new freely available computer-aided polyp detection system in clinical practice
Thomas J Lux, Michael Banck, Zita Saßmannshausen, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 16) with videos related to
Sort By:
Page
of 2
Artificial Intelligence in Medicine
|
November 18, 2025
Enhancing transformer-based architectures with geometric deep learning for colonoscopic polyp size classification using transfer learning
Adrian Krenzer, Stefan Heil, Frank Puppe
Studies in Health Technology and Informatics
|
May 27, 2021
Semi-Automated Machine Learning Video Annotation for Gastroenterologists
Adrian Krenzer, Kevin Makowski, Amar Hekalo, et al.
BMC Medical Imaging
|
April 20, 2023
Automated classification of polyps using deep learning architectures and few-shot learning
Adrian Krenzer, Stefan Heil, Daniel Fitting, et al.
Gastrointestinal Endoscopy
|
December 20, 2021
New concept for colonoscopy including side optics and artificial intelligence
Joel Troya, Adrian Krenzer, Krzysztof Flisikowski, et al.
Biomedical Engineering Online
|
May 25, 2022
Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists
Adrian Krenzer, Kevin Makowski, Amar Hekalo, et al.
United European Gastroenterology Journal
|
May 5, 2022
Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions
Markus Brand, Joel Troya, Adrian Krenzer, et al.
Digestion
|
June 29, 2022
Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies
Markus Brand, Joel Troya, Adrian Krenzer, et al.
Journal of Imaging
|
February 24, 2023
A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks
Adrian Krenzer, Michael Banck, Kevin Makowski, et al.
Endoscopy
|
August 2, 2023
Direct comparison of multiple computer-aided polyp detection systems
Joel Troya, Boban Sudarevic, Adrian Krenzer, et al.
International Journal of Colorectal Disease
|
May 11, 2022
Pilot study of a new freely available computer-aided polyp detection system in clinical practice
Thomas J Lux, Michael Banck, Zita Saßmannshausen, et al.
Page
of 2