Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Robert Mendel"'
Autor:
Christoph Römmele, Robert Mendel, Caroline Barrett, Hans Kiesl, David Rauber, Tobias Rückert, Lisa Kraus, Jakob Heinkele, Christine Dhillon, Bianca Grosser, Friederike Prinz, Julia Wanzl, Carola Fleischmann, Sandra Nagl, Elisabeth Schnoy, Jakob Schlottmann, Evan S. Dellon, Helmut Messmann, Christoph Palm, Alanna Ebigbo
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features o
Externí odkaz:
https://doaj.org/article/75e9ae3167ac4cab9b8e6bc2a18ecf88
Autor:
Alanna Ebigbo, Christoph Palm, Andreas Probst, Robert Mendel, Johannes Manzeneder, Friederike Prinz, Luis A. de Souza, João P. Papa, Peter Siersema, Helmut Messmann
Publikováno v:
Endoscopy International Open, Vol 07, Iss 12, Pp E1616-E1623 (2019)
Background and aim The growing number of publications on the application of artificial intelligence (AI) in medicine underlines the enormous importance and potential of this emerging field of research. In gastrointestinal endoscopy, AI has been appli
Externí odkaz:
https://doaj.org/article/aaffea78c8ff4947a7990684eba83f32
Publikováno v:
Computers in Biology and Medicine. 154:106585
Autor:
David Rauber, Robert Mendel, Markus W. Scheppach, Alanna Ebigbo, Helmut Messmann, Christoph Palm
Publikováno v:
Informatik aktuell ISBN: 9783658369316
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59fad691c5edc0f167c785111f2698a8
https://doi.org/10.1007/978-3-658-36932-3_25
https://doi.org/10.1007/978-3-658-36932-3_25
Autor:
Alanna Ebigbo, Robert Mendel, Markus W Scheppach, Andreas Probst, Neal Shahidi, Friederike Prinz, Carola Fleischmann, Christoph Römmele, Stefan Karl Goelder, Georg Braun, David Rauber, Tobias Rueckert, Luis A de Souza, Joao Papa, Michael Byrne, Christoph Palm, Helmut Messmann
In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::759ccaaf5f43d3641b339d5b0583e500
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/98670
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/98670
Autor:
Alanna Ebigbo, Robert Mendel, Andreas Probst, Michael Meinikheim, Michael F. Byrne, Helmut Messmann, Christoph Palm
Publikováno v:
Endoscopy. 54(10)
Autor:
Tobias Rückert, Christoph Palm, Alanna Ebigbo, Christoph Römmele, Robert Mendel, Michael F. Byrne, David Rauber, Helmut Messmann
Publikováno v:
ESGE Days 2021.
Aims Eosinophilic esophagitis (EoE) is easily missed during endoscopy, either because physicians are not familiar with its endoscopic features or the morphologic changes are too subtle. In this preliminary paper, we present the first attempt to detec
Autor:
Robert Mendel, Michael F. Byrne, David Rauber, Markus Scheppach, Christoph Palm, Helmut Messmann, Alanna Ebigbo
Publikováno v:
ESGE Days 2021.
Aims Celiac disease (CD) is a complex condition caused by an autoimmune reaction to ingested gluten. Due to its polymorphic manifestation and subtle endoscopic presentation, the diagnosis is difficult and thus the disorder is underreported. We aimed
Autor:
Alanna Ebigbo, Robert Mendel, Luis Antonio De Souza, Christoph Palm, Andreas Probst, Leandro A. Passos, João Paulo Papa, Helmut Messmann
Publikováno v:
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Made available in DSpace on 2019-10-06T17:02:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fund
Publikováno v:
Bildverarbeitung für die Medizin 2021 ISBN: 9783658331979
Bildverarbeitung für die Medizin
Bildverarbeitung für die Medizin
Pixel-level classification is an essential part of computer vision. For learning from labeled data, many powerful deep learning models have been developed recently. In this work, we augment such supervised segmentation models by allowing them to lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c42d4d18b1bda429092edbea647a573f
https://doi.org/10.1007/978-3-658-33198-6_43
https://doi.org/10.1007/978-3-658-33198-6_43