Matthias Wilms

Fairness-related performance and explainability effects in deep learning models for brain image analysis

2022 · 37 Zit. · Journal of Medical Imaging

Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging

2024 · 21 Zit. · Journal of the American Medical Informatics Association

Disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis

2022 · 17 Zit. · Lecture notes in computer science

Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge

2025 · 6 Zit. · Nature Communications

Understanding privacy risks in typical deep learning models for medical image analysis

2021 · 4 Zit.

Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging

2023 · 2 Zit. · arXiv (Cornell University)

Connecting algorithmic fairness and fair outcomes in a sociotechnical simulation case study of AI-assisted healthcare

2025 · 0 Zit. · Nature Communications

Simulating Inter-observer Variability Across Clinical Experience Levels for Brain Tumour Segmentation

2025 · 0 Zit. · Lecture notes in computer science

Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis

2024 · 0 Zit. · Lecture notes in computer science