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You search for a phrase ""Woerl, Ann-Christin"" according to the criterion: Author


Showing 1-3 from 3 results
Title :
Deep Learning Predicts Molecular Subtype of Muscle-invasive Bladder Cancer from Conventional Histopathological Slides.
Authors :
Woerl AC; Institute of Pathology, University Medical Center Mainz, Mainz, Germany; Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
Eckstein M; Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Geiger J; Institute of Pathology, University Medical Center Mainz, Mainz, Germany; Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
Wagner DC; Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
Daher T; Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
Stenzel P; Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
Fernandez A; Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
Hartmann A; Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Wand M; Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
Roth W; Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
Foersch S; Institute of Pathology, University Medical Center Mainz, Mainz, Germany. Electronic address: .
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Source :
European urology [Eur Urol] 2020 Aug; Vol. 78 (2), pp. 256-264. Date of Electronic Publication: 2020 Apr 27.
Publication Type :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Deep Learning*
Urinary Bladder Neoplasms/*classification
Urinary Bladder Neoplasms/*genetics
Forecasting ; Humans ; Molecular Diagnostic Techniques ; Neoplasm Invasiveness ; Urinary Bladder Neoplasms/diagnosis ; Urinary Bladder Neoplasms/pathology
Academic Journal
    Showing 1-3 from 3 results

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