| The liver tumor segmentation benchmark (LITS) P Bilic, PF Christ, E Vorontsov, G Chlebus, H Chen, Q Dou, CW Fu, X Han, ... arXiv preprint arXiv:1901.04056, 2019 | 723* | 2019 |
| Secure, privacy-preserving and federated machine learning in medical imaging GA Kaissis, MR Makowski, D Rückert, RF Braren Nature Machine Intelligence 2 (6), 305-311, 2020 | 582 | 2020 |
| Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks PF Christ, F Ettlinger, F Grün, MEA Elshaera, J Lipkova, S Schlecht, ... arXiv preprint arXiv:1702.05970, 2017 | 391 | 2017 |
| End-to-end privacy preserving deep learning on multi-institutional medical imaging G Kaissis, A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, ... Nature Machine Intelligence 3 (6), 473-484, 2021 | 186 | 2021 |
| Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study Q Dou, TY So, M Jiang, Q Liu, V Vardhanabhuti, G Kaissis, Z Li, W Si, ... NPJ digital medicine 4 (1), 60, 2021 | 141 | 2021 |
| Pysyft: A library for easy federated learning A Ziller, A Trask, A Lopardo, B Szymkow, B Wagner, E Bluemke, ... Federated Learning Systems: Towards Next-Generation AI, 111-139, 2021 | 110 | 2021 |
| Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort E Burian, F Jungmann, GA Kaissis, FK Lohöfer, CD Spinner, T Lahmer, ... Journal of clinical medicine 9 (5), 1514, 2020 | 77 | 2020 |
| Medical imaging deep learning with differential privacy A Ziller, D Usynin, R Braren, M Makowski, D Rueckert, G Kaissis Scientific Reports 11 (1), 13524, 2021 | 74 | 2021 |
| A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging G Kaissis, S Ziegelmayer, F Lohöfer, H Algül, M Eiber, W Weichert, ... European radiology experimental 3 (1), 1-9, 2019 | 60 | 2019 |
| A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy G Kaissis, S Ziegelmayer, F Lohöfer, K Steiger, H Algül, A Muckenhuber, ... PloS one 14 (10), e0218642, 2019 | 57 | 2019 |
| Image-based molecular phenotyping of pancreatic ductal adenocarcinoma GA Kaissis, S Ziegelmayer, FK Lohöfer, FN Harder, F Jungmann, D Sasse, ... Journal of Clinical Medicine 9 (3), 724, 2020 | 43 | 2020 |
| SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks PF Christ, F Ettlinger, G Kaissis, S Schlecht, F Ahmaddy, F Grün, ... 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 38 | 2017 |
| Ratchet: Medical transformer for chest x-ray diagnosis and reporting B Hou, G Kaissis, RM Summers, B Kainz Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 35 | 2021 |
| Joint imaging platform for federated clinical data analytics J Scherer, M Nolden, J Kleesiek, J Metzger, K Kades, V Schneider, ... JCO clinical cancer informatics 4, 1027-1038, 2020 | 33 | 2020 |
| Implementing cell-free DNA of pancreatic cancer patient–derived organoids for personalized oncology Z Dantes, HY Yen, N Pfarr, C Winter, K Steiger, A Muckenhuber, A Hennig, ... JCI insight 5 (15), 2020 | 32 | 2020 |
| Joint learning of localized representations from medical images and reports P Müller, G Kaissis, C Zou, D Rueckert European Conference on Computer Vision, 685-701, 2022 | 29 | 2022 |
| A primer on machine learning J Kleesiek, JM Murray, C Strack, G Kaissis, R Braren Der Radiologe 60, 24-31, 2020 | 27* | 2020 |
| Magnetic resonance cholangiopancreatography at 3 Tesla: image quality comparison between 3D compressed sensing and 2D single-shot acquisitions FK Lohöfer, GA Kaissis, M Rasper, C Katemann, A Hock, JM Peeters, ... European Journal of Radiology 115, 53-58, 2019 | 27 | 2019 |
| Accuracy of calcium scoring calculated from contrast-enhanced coronary computed tomography angiography using a dual-layer spectral CT: a comparison of calcium scoring from real … J Nadjiri, G Kaissis, F Meurer, F Weis, KL Laugwitz, AS Straeter, ... PLoS One 13 (12), e0208588, 2018 | 27 | 2018 |
| Adversarial interference and its mitigations in privacy-preserving collaborative machine learning D Usynin, A Ziller, M Makowski, R Braren, D Rueckert, B Glocker, ... Nature Machine Intelligence 3 (9), 749-758, 2021 | 26 | 2021 |
Rickmer BrarenTechnical University MunichAdresse e-mail validée de tum.de
