Georgios Kaissis

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

2020 · 1.281 Zit. · Nature Machine Intelligence

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

2024 · 510 Zit. · Nature Medicine

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

2021 · 460 Zit. · Nature Machine Intelligence

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

2025 · 284 Zit. · BMJ

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

2021 · 270 Zit. · npj Digital Medicine

Medical imaging deep learning with differential privacy

2021 · 149 Zit. · Scientific Reports

Encrypted federated learning for secure decentralized collaboration in cancer image analysis

2023 · 80 Zit. · Medical Image Analysis

Joint Imaging Platform for Federated Clinical Data Analytics

2020 · 71 Zit. · JCO Clinical Cancer Informatics

Reconciling privacy and accuracy in AI for medical imaging

2024 · 58 Zit. · Nature Machine Intelligence

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

2023 · 38 Zit. · arXiv (Cornell University)

Wie funktioniert maschinelles Lernen?

2019 · 20 Zit. · Der Radiologe

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

2022 · 16 Zit. · European Radiology

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

2023 · 16 Zit. · Radiology Artificial Intelligence

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

2022 · 16 Zit. · Research Square

Wie funktioniert Radiomics?

2019 · 13 Zit. · Der Radiologe