Klaus Maier‐Hein

The Medical Segmentation Decathlon

2022 · 1.111 Zit. · Nature Communications

MONAI: An open-source framework for deep learning in healthcare

2022 · 425 Zit. · arXiv (Cornell University)

Why rankings of biomedical image analysis competitions should be interpreted with care

2018 · 346 Zit. · Nature Communications

Metrics reloaded: recommendations for image analysis validation

2024 · 344 Zit. · Nature Methods

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update

2024 · 247 Zit. · Radiology Artificial Intelligence

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

2025 · 222 Zit. · BMJ

Understanding metric-related pitfalls in image analysis validation

2024 · 154 Zit. · Nature Methods

Joint Imaging Platform for Federated Clinical Data Analytics

2020 · 70 Zit. · JCO Clinical Cancer Informatics

Metrics reloaded: Recommendations for image analysis validation

2022 · 62 Zit. · arXiv (Cornell University)

Deep Learning–based Assessment of Oncologic Outcomes from Natural Language Processing of Structured Radiology Reports

2022 · 48 Zit. · Radiology Artificial Intelligence

The Federated Tumor Segmentation (FeTS) Challenge

2021 · 42 Zit. · arXiv (Cornell University)

Extending nnU-Net Is All You Need

2023 · 31 Zit. · Informatik aktuell

The importance of machine learning in autonomous actions for surgical decision making

2022 · 21 Zit. · Artificial Intelligence Surgery

Understanding metric-related pitfalls in image analysis validation

2023 · 20 Zit. · arXiv (Cornell University)

Real-world federated learning in radiology: hurdles to overcome and benefits to gain

2024 · 13 Zit. · Journal of the American Medical Informatics Association