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Jochen S Utikal

Showing results (21-30 of 47) with videos related to

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European Journal of Cancer (Oxford, England : 1990)|July 21, 2019
Deep learning outperformed 11 pathologists in the classification of histopathological melanoma imagesAchim Hekler, Jochen S Utikal, Alexander H Enk, et al.
Blood|May 22, 2023
Dimethyl fumarate treatment in relapsed and refractory cutaneous T-cell lymphoma: a multicenter phase 2 studyJan P Nicolay, Susanne Melchers, Jana D Albrecht, et al.
European Journal of Cancer (Oxford, England : 1990)|September 14, 2019
Superior skin cancer classification by the combination of human and artificial intelligenceAchim Hekler, Jochen S Utikal, Alexander H Enk, et al.
BJU International|March 11, 2021
Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancerFrederik Wessels, Max Schmitt, Eva Krieghoff-Henning, et al.
Plos One|August 17, 2022
Deep learning can predict survival directly from histology in clear cell renal cell carcinomaFrederik Wessels, Max Schmitt, Eva Krieghoff-Henning, et al.
World Journal of Urology|June 29, 2023
A self-supervised vision transformer to predict survival from histopathology in renal cell carcinomaFrederik Wessels, Max Schmitt, Eva Krieghoff-Henning, et al.
Journal of Medical Internet Research|September 11, 2020
Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey StudyRoman C Maron, Jochen S Utikal, Achim Hekler, et al.
European Journal of Cancer (Oxford, England : 1990)|February 20, 2017
Ipilimumab alone or in combination with nivolumab after progression on anti-PD-1 therapy in advanced melanomaLisa Zimmer, Susmitha Apuri, Zeynep Eroglu, et al.
Nature Communications|May 21, 2025
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking studyTirtha Chanda, Sarah Haggenmueller, Tabea-Clara Bucher, et al.
European Journal of Cancer (Oxford, England : 1990)|July 23, 2021
Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumoursTitus J Brinker, Lennard Kiehl, Max Schmitt, et al.
Pageof 5

Showing results (21-30 of 47) with videos related to

Sort By:
Pageof 5
European Journal of Cancer (Oxford, England : 1990)|July 21, 2019
Deep learning outperformed 11 pathologists in the classification of histopathological melanoma imagesAchim Hekler, Jochen S Utikal, Alexander H Enk, et al.
Blood|May 22, 2023
Dimethyl fumarate treatment in relapsed and refractory cutaneous T-cell lymphoma: a multicenter phase 2 studyJan P Nicolay, Susanne Melchers, Jana D Albrecht, et al.
European Journal of Cancer (Oxford, England : 1990)|September 14, 2019
Superior skin cancer classification by the combination of human and artificial intelligenceAchim Hekler, Jochen S Utikal, Alexander H Enk, et al.
BJU International|March 11, 2021
Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancerFrederik Wessels, Max Schmitt, Eva Krieghoff-Henning, et al.
Plos One|August 17, 2022
Deep learning can predict survival directly from histology in clear cell renal cell carcinomaFrederik Wessels, Max Schmitt, Eva Krieghoff-Henning, et al.
World Journal of Urology|June 29, 2023
A self-supervised vision transformer to predict survival from histopathology in renal cell carcinomaFrederik Wessels, Max Schmitt, Eva Krieghoff-Henning, et al.
Journal of Medical Internet Research|September 11, 2020
Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey StudyRoman C Maron, Jochen S Utikal, Achim Hekler, et al.
European Journal of Cancer (Oxford, England : 1990)|February 20, 2017
Ipilimumab alone or in combination with nivolumab after progression on anti-PD-1 therapy in advanced melanomaLisa Zimmer, Susmitha Apuri, Zeynep Eroglu, et al.
Nature Communications|May 21, 2025
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking studyTirtha Chanda, Sarah Haggenmueller, Tabea-Clara Bucher, et al.
European Journal of Cancer (Oxford, England : 1990)|July 23, 2021
Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumoursTitus J Brinker, Lennard Kiehl, Max Schmitt, et al.
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