TU Dortmund University

What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research

Markus Langer, Daniel Oster, Timo Speith et al.

2021 · 545 Zit.

Machine learning and conventional statistics: making sense of the differences

Christophe Ley, R. Kyle Martin, Ayoosh Pareek et al.

2022 · 181 Zit.

Explainable AI in medical imaging: An overview for clinical practitioners – Beyond saliency-based XAI approaches

Katarzyna Borys, Yasmin Alyssa Schmitt, Meike Nauta et al.

2023 · 160 Zit.

Explainable AI in medical imaging: An overview for clinical practitioners – Saliency-based XAI approaches

Katarzyna Borys, Yasmin Alyssa Schmitt, Meike Nauta et al.

2023 · 123 Zit.

Privacy-preserving large language models for structured medical information retrieval

Isabella C. Wiest, Dyke Ferber, Jiefu Zhu et al.

2024 · 80 Zit.

Artificial intelligence and machine learning: an introduction for orthopaedic surgeons

R. Kyle Martin, Christophe Ley, Ayoosh Pareek et al.

2021 · 70 Zit.

Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals

Matthias Klumpp, Marcus Hintze, Milla Immonen et al.

2021 · 68 Zit.

Ossification area localization in pediatric hand radiographs using deep neural networks for object detection

Sven Koitka, Aydın Demircioğlu, Moon Kim et al.

2018 · 29 Zit.

From Text to Tables: A Local Privacy Preserving Large Language Model for Structured Information Retrieval from Medical Documents

Isabella C. Wiest, Dyke Ferber, Jiefu Zhu et al.

2023 · 27 Zit.

COVID-19: A Survey on Public Medical Imaging Data Resources

Roman Kalkreuth, Paul Kaufmann

2020 · 25 Zit.

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks

Felix J. Dorfner, Amin Dada, Felix Busch et al.

2025 · 20 Zit.

Causality and scientific explanation of artificial intelligence systems in biomedicine

Florian J. Boge, Axel Mosig

2024 · 13 Zit.

Can Machine Learning from Real-World Data Support Drug Treatment Decisions? A Prediction Modeling Case for Direct Oral Anticoagulants

Andreas D. Meid, Lucas Wirbka, ARMIN Study Group et al.

2021 · 12 Zit.

Machine learning with real-world HR data: mitigating the trade-off between predictive performance and transparency

Ansgar Heidemann, Svenja M. Hülter, Michael Tekieli

2024 · 10 Zit.

The Epistemic Cost of Opacity: How the Use of Artificial Intelligence Undermines the Knowledge of Medical Doctors in High-Stakes Contexts

Eva Schmidt, Paul Martin Putora, Rianne Fijten

2025 · 7 Zit.