Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer

Authors:	Frederik Wessels Max Schmitt Eva Krieghoff-Henning Tanja Jutzi Thomas S. Worst Frank Waldbillig Manuel Neuberger Roman C. Maron Matthias Steeg Timo Gaiser Achim Hekler Jochen S. Utikal Christof von Kalle Stefan Fröhling Maurice S. Michel Philipp Nuhn Titus J. Brinker

Affiliation:	1. Digital Biomarkers for Oncology Group, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany;2. Department of Urology and Urological Surgery, Medical Faculty Mannheim of Heidelberg University, University Medical Center Mannheim, Mannheim, Germany;3. Institute of Pathology, Medical Faculty Mannheim of Heidelberg University, University Medical Center Mannheim, Mannheim, Germany;4. Skin Cancer Unit, German Cancer Research Center (DKFZ), Heidelberg, Germany Department of Dermatology, Venereology and Allergology, University Medical Center Mannheim, University of Heidelberg, Heidelberg, Germany;5. Department of Clinical-Translational Sciences, Berlin Institute of Health (BIH), Charité University Medicine, Berlin, Germany;6. National Center for Tumor Diseases, German Cancer Research Center, Heidelberg, Germany

Abstract:

Keywords:	prostatic neoplasms machine learning deep learning artificial intelligence convolutional neural network neoplasm metastasis #ProstateCancer #PCSM #uroonc