| 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 | 1911* | 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 | 1610 | 2020 |
| Evaluation and mitigation of the limitations of large language models in clinical decision-making P Hager, F Jungmann, R Holland, K Bhagat, I Hubrecht, M Knauer, ... Nature medicine 30 (9), 2613-2622, 2024 | 591 | 2024 |
| 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 | 560 | 2021 |
| 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 | 512 | 2017 |
| 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 | 357 | 2021 |
| FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare K Lekadir, AF Frangi, AR Porras, B Glocker, C Cintas, CP Langlotz, ... bmj 388, 2025 | 346 | 2025 |
| Interactive and explainable region-guided radiology report generation T Tanida, P Müller, G Kaissis, D Rueckert Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 295 | 2023 |
| 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 | 289 | 2021 |
| 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 | 228 | 2021 |
| A distinct stimulatory cDC1 subpopulation amplifies CD8+ T cell responses in tumors for protective anti-cancer immunity P Meiser, MA Knolle, A Hirschberger, GP de Almeida, F Bayerl, S Lacher, ... Cancer Cell 41 (8), 1498-1515. e10, 2023 | 190 | 2023 |
| 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 | 136 | 2022 |
| Relationformer: A Unified Framework for Image-to-Graph Generation S Shit, R Koner, B Wittmann, J Paetzold, I Ezhov, H Li, J Pan, ... European conference on computer vision, 422-439, 2022 | 100 | 2022 |
| Encrypted federated learning for secure decentralized collaboration in cancer image analysis D Truhn, ST Arasteh, OL Saldanha, G Müller-Franzes, F Khader, P Quirke, ... Medical image analysis 92, 103059, 2024 | 99 | 2024 |
| Ratchet: Medical transformer for chest x-ray diagnosis and reporting B Hou, G Kaissis, RM Summers, B Kainz International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 95 | 2021 |
| Federated electronic health records for the European Health Data Space R Raab, A Küderle, A Zakreuskaya, AD Stern, J Klucken, G Kaissis, ... The Lancet Digital Health 5 (11), e840-e847, 2023 | 92 | 2023 |
| 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 | 91 | 2020 |
| 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 | 85 | 2020 |
| 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), 41, 2019 | 81 | 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 | 81 | 2019 |
Daniel RueckertTechnical University of Munich and Imperial College LondonVerified email at tum.de
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