Kaissis, Georgios

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

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Lekadir, K., Frangi, A. F., Porras, A. R., Glocker, B., Cintas, C., Langlotz, C. P., Weicken, E., Asselbergs, F. W., Prior, F., Collins, G. S., et al. (2025) · BMJ

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 957

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

PySyft: A Library for Easy Federated Learning

Ziller, A., Trask, A., Lopardo, A., Szymkow, B., Wagner, B., Bluemke, E., Nounahon, J.-M., Passerat-Palmbach, J., Prakash, K., Rose, N., et al. (2021) · Studies in Computational Intelligence

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 246

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

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

Attack-Aware Noise Calibration for Differential Privacy

Kulynych, B., Gomez, J. F., Kaissis, G., Calmon, F. D. P., & Troncoso, C. (2024) · arXiv

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 13

Weakly Supervised Object Detection in Chest X-Rays With Differentiable ROI Proposal Networks and Soft ROI Pooling

Müller, P., Meissen, F., Kaissis, G., & Rueckert, D. (2025) · IEEE Transactions on Medical Imaging

COVID-19 diagnosis using AIAdvanced Neural Network Applications

Cited by 8