Medical students' attitude towards artificial intelligence: a multicentre survey DP dos Santos, D Giese, S Brodehl, SH Chon, W Staab, R Kleinert, ... European Radiology, 1-7, 2018 | 476 | 2018 |
Structured report data can be used to develop deep learning algorithms: a proof of concept in ankle radiographs D Pinto dos Santos, S Brodehl, B Baeßler, G Arnhold, T Dratsch, SH Chon, ... Insights into imaging 10, 1-8, 2019 | 43 | 2019 |
Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study A Mähringer‐Kunz, F Wagner, F Hahn, A Weinmann, S Brodehl, ... Liver International 40 (3), 694-703, 2020 | 36 | 2020 |
End-to-end prediction of lightning events from geostationary satellite images S Brodehl, R Müller, E Schömer, P Spichtinger, M Wand Remote Sensing 14 (15), 3760, 2022 | 11 | 2022 |
Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network T Dratsch, M Korenkov, D Zopfs, S Brodehl, B Baessler, D Giese, ... European radiology 31, 1812-1818, 2021 | 10 | 2021 |
Studying the evolution of neural activation patterns during training of feed-forward relu networks D Hartmann, D Franzen, S Brodehl Frontiers in Artificial Intelligence 4, 642374, 2021 | 4 | 2021 |
Workflow-centred open-source fully automated lung volumetry in chest CT F Jungmann, S Brodehl, R Buhl, P Mildenberger, E Schömer, C Düber, ... Clinical Radiology 75 (1), 78. e1-78. e7, 2020 | 4 | 2020 |
ActCooLR–High-Level Learning Rate Schedules using Activation Pattern Temperature D Hartmann, S Brodehl, M Wand | 1 | 2021 |