Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Jochen S Utikal"'
Autor:
Lukas Heinlein, Roman C. Maron, Achim Hekler, Sarah Haggenmüller, Christoph Wies, Jochen S. Utikal, Friedegund Meier, Sarah Hobelsberger, Frank F. Gellrich, Mildred Sergon, Axel Hauschild, Lars E. French, Lucie Heinzerling, Justin G. Schlager, Kamran Ghoreschi, Max Schlaak, Franz J. Hilke, Gabriela Poch, Sören Korsing, Carola Berking, Markus V. Heppt, Michael Erdmann, Sebastian Haferkamp, Konstantin Drexler, Dirk Schadendorf, Wiebke Sondermann, Matthias Goebeler, Bastian Schilling, Eva Krieghoff-Henning, Titus J. Brinker
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-9 (2024)
Abstract Background Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence (AI) has proven to be helpful for enhancing melano
Externí odkaz:
https://doaj.org/article/b94e12d429514a5caf386ed1f4f44417
Autor:
Eva Winkler
Publikováno v:
Ethik in der Medizin. 34:137-140
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e048e5434a88a7453f0da3d2f414a3f4
https://doi.org/10.1007/s00481-022-00685-y
https://doi.org/10.1007/s00481-022-00685-y
Autor:
Winkler, Eva C.
Publikováno v:
Ethik in Der Medizin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmc_________::cdc5cf8da93bbea8b701a53208a97d00
http://europepmc.org/articles/PMC8805420
http://europepmc.org/articles/PMC8805420
Autor:
Tirtha Chanda, Katja Hauser, Sarah Hobelsberger, Tabea-Clara Bucher, Carina Nogueira Garcia, Christoph Wies, Harald Kittler, Philipp Tschandl, Cristian Navarrete-Dechent, Sebastian Podlipnik, Emmanouil Chousakos, Iva Crnaric, Jovana Majstorovic, Linda Alhajwan, Tanya Foreman, Sandra Peternel, Sergei Sarap, İrem Özdemir, Raymond L. Barnhill, Mar Llamas-Velasco, Gabriela Poch, Sören Korsing, Wiebke Sondermann, Frank Friedrich Gellrich, Markus V. Heppt, Michael Erdmann, Sebastian Haferkamp, Konstantin Drexler, Matthias Goebeler, Bastian Schilling, Jochen S. Utikal, Kamran Ghoreschi, Stefan Fröhling, Eva Krieghoff-Henning, Reader Study Consortium, Titus J. Brinker
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet oft
Externí odkaz:
https://doaj.org/article/a7c398cf0b3b4b35ad5fc17b7f22b907
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
Mutations in the NRAS gene are common alterations in malignant melanoma. However, there are no specific treatment options approved for NRAS-mutated melanoma patients besides immune checkpoint inhibition. Since preclinical data suggests a synergistic
Externí odkaz:
https://doaj.org/article/b1bd112b400144c08b8558480e671f81
Autor:
Dirk Schadendorf, Lucie Heinzerling, Jessica C Hassel, Lisa Zimmer, Ralf Gutzmer, Lisa Villabona, Selma Ugurel, Thomas Eigentler, Peter Mohr, Thilo Gambichler, Patrick Terheyden, Sebastian Haferkamp, Claudia Pfoehler, Carmen Loquai, Jürgen Christian Becker, Ulrike Leiter, Hans-Ulrich Schildhaus, Ivelina Spassova, Linda Kubat, Annalena Mohr, Hannah Björn Andtback, Jochen S Utikal, Kai Horny, Daniel Habermann, Daniel Hoffmann
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 10, Iss 1 (2022)
Externí odkaz:
https://doaj.org/article/9d5ed971c944418f96838e599806293f
Autor:
Frederik Wessels, Max Schmitt, Eva Krieghoff-Henning, Jakob N Kather, Malin Nientiedt, Maximilian C Kriegmair, Thomas S Worst, Manuel Neuberger, Matthias Steeg, Zoran V Popovic, Timo Gaiser, Christof von Kalle, Jochen S Utikal, Stefan Fröhling, Maurice S Michel, Philipp Nuhn, Titus J Brinker
Publikováno v:
PLoS ONE, Vol 17, Iss 8, p e0272656 (2022)
For clear cell renal cell carcinoma (ccRCC) risk-dependent diagnostic and therapeutic algorithms are routinely implemented in clinical practice. Artificial intelligence-based image analysis has the potential to improve outcome prediction and thereby
Externí odkaz:
https://doaj.org/article/dc38b43529124025af4013dff0dabcb4
Autor:
Lucas Schneider, Christoph Wies, Eva I. Krieghoff-Henning, Tabea-Clara Bucher, Jochen S. Utikal, Dirk Schadendorf, Titus J. Brinker
Publikováno v:
European Journal of Cancer. 183:131-138
Background: In machine learning, multimodal classifiers can provide more generalised performance than unimodal classifiers. In clinical practice, physicians usually also rely on a range of information from different examinations for diagnosis. In thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eef662a5a0213ae32176a07af832f6fa
https://doi.org/10.1016/j.ejca.2023.01.021
https://doi.org/10.1016/j.ejca.2023.01.021
Autor:
Flavia-Bianca Cristian, Alexandra Köppel, Johannes Janssen, Jochen S. Utikal, Gudrun A. Rappold, Simone Berkel
Publikováno v:
Stem Cell Research, Vol 49, Iss , Pp 102004- (2020)
Two human induced pluripotent stem cell lines (hiPSC) were generated by reprogramming fibroblasts isolated from a skin biopsy taken from a female patient diagnosed with autism spectrum disorder (ASD) and intellectual disability (ID). This patient har
Externí odkaz:
https://doaj.org/article/35929a2c8fe846e5aff34e08c4c9b977
Autor:
Achim Hekler, Jakob N. Kather, Eva Krieghoff-Henning, Jochen S. Utikal, Friedegund Meier, Frank F. Gellrich, Julius Upmeier zu Belzen, Lars French, Justin G. Schlager, Kamran Ghoreschi, Tabea Wilhelm, Heinz Kutzner, Carola Berking, Markus V. Heppt, Sebastian Haferkamp, Wiebke Sondermann, Dirk Schadendorf, Bastian Schilling, Benjamin Izar, Roman Maron, Max Schmitt, Stefan Fröhling, Daniel B. Lipka, Titus J. Brinker
Publikováno v:
Frontiers in Medicine, Vol 7 (2020)
Recent studies have shown that deep learning is capable of classifying dermatoscopic images at least as well as dermatologists. However, many studies in skin cancer classification utilize non-biopsy-verified training images. This imperfect ground tru
Externí odkaz:
https://doaj.org/article/7c8a3d919b4d4e7da94887fa5381fe8d