Braren, Rickmer

Secure, privacy-preserving and federated machine learning in medical imaging

Kaissis, G. A., Makowski, M. R., Rückert, D., & Braren, R. F. (2020) · Nature Machine Intelligence

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 1,676

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2019) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2023) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

Evaluation and mitigation of the limitations of large language models in clinical decision-making

Hager, P., Jungmann, F., Holland, R., Bhagat, K., Hubrecht, I., Knauer, M., Vielhauer, J., Makowski, M., Braren, R., Kaissis, G., et al. (2024) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 798

End-to-end privacy preserving deep learning on multi-institutional medical imaging

Kaissis, G., Ziller, A., Passerat-Palmbach, J., Ryffel, T., Usynin, D., Trask, A., Lima, I., Mancuso, J., Jungmann, F., Steinborn, M.-M., et al. (2021) · Nature Machine Intelligence

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 513

Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study

Dou, Q., So, T. Y., Jiang, M., Liu, Q., Vardhanabhuti, V., Kaissis, G., Li, Z., Si, W., Lee, H. H. C., Yu, K., et al. (2021) · npj Digital Medicine

COVID-19 diagnosis using AIPrivacy-Preserving Technologies in Data

Cited by 278

Medical imaging deep learning with differential privacy

Ziller, A., Usynin, D., Braren, R., Makowski, M., Rueckert, D., & Kaissis, G. (2021) · Scientific Reports

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 172

Cell-autonomous requirement for β1 integrin in endothelial cell adhesion, migration and survival during angiogenesis in mice

Carlson, T. R., Hu, H., Braren, R., Kim, Y. H., & Wang, R. A. (2008) · Development

Cell Adhesion Molecules ResearchAngiogenesis and VEGF in Cancer

Cited by 157

A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging

Kaissis, G., Ziegelmayer, S., Lohöfer, F., Algül, H., Eiber, M., Weichert, W., Schmid, R., Friess, H., Rummeny, E., Ankerst, D., et al. (2019) · European Radiology Experimental

Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis

Cited by 79

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy

Kaissis, G., Ziegelmayer, S., Lohöfer, F., Steiger, K., Algül, H., Muckenhuber, A., Yen, H.-Y., Rummeny, E., Friess, H., Schmid, R., et al. (2019) · PLOS ONE

Radiomics and Machine Learning in Medical ImagingPancreatic and Hepatic Oncology Research

Cited by 76