Georgios Kaissis

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

2020 · 1.207 Zit. · Nature Machine Intelligence

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

2021 · 433 Zit. · Nature Machine Intelligence

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

2024 · 432 Zit. · Nature Medicine

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

2021 · 262 Zit. · npj Digital Medicine

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

2025 · 218 Zit. · BMJ

Medical imaging deep learning with differential privacy

2021 · 143 Zit. · Scientific Reports

Encrypted federated learning for secure decentralized collaboration in cancer image analysis

2023 · 73 Zit. · Medical Image Analysis

Joint Imaging Platform for Federated Clinical Data Analytics

2020 · 70 Zit. · JCO Clinical Cancer Informatics

Reconciling privacy and accuracy in AI for medical imaging

2024 · 52 Zit. · Nature Machine Intelligence

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

2023 · 38 Zit. · arXiv (Cornell University)

Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging

2024 · 33 Zit. · Communications Medicine

Wie funktioniert maschinelles Lernen?

2019 · 20 Zit. · Der Radiologe

Differentially private federated deep learning for multi-site medical image segmentation

2022 · 16 Zit. · Research Square (Research Square)

Securing Collaborative Medical AI by Using Differential Privacy: Domain Transfer for Classification of Chest Radiographs

2023 · 15 Zit. · Radiology Artificial Intelligence

Algorithmic transparency and interpretability measures improve radiologists’ performance in BI-RADS 4 classification

2022 · 14 Zit. · European Radiology