IT University of Copenhagen

Machine learning for medical imaging: methodological failures and recommendations for the future

Gaël Varoquaux, Veronika Cheplygina

2022 · 542 Zit.

Metrics reloaded: recommendations for image analysis validation

Lena Maier‐Hein, Annika Reinke, Patrick Godau et al.

2024 · 338 Zit.

Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation

Jichen Zhu, Antonios Liapis, Sebastian Risi et al.

2018 · 235 Zit.

Understanding metric-related pitfalls in image analysis validation

Annika Reinke, Minu D. Tizabi, Michael Baumgartner et al.

2024 · 154 Zit.

Designing Participatory AI: Creative Professionals’ Worries and Expectations about Generative AI

Nanna Inie, Jeanette Falk, Steve Tanimoto

2023 · 101 Zit.

Governing AI‐Driven Health Research: Are IRBs Up to the Task?

Phoebe Friesen, Rachel Douglas‐Jones, Mason Marks et al.

2021 · 46 Zit.

The medical profession transformed by artificial intelligence: Qualitative study

Lina Mosch, Daniel Fürstenau, Jenny Brandt et al.

2022 · 28 Zit.

Exploring needs and challenges for AI in nursing care – results of an explorative sequential mixed methods study

Kathrin Seibert, Dominik Domhoff, Daniel Fürstenau et al.

2023 · 27 Zit.

Understanding metric-related pitfalls in image analysis validation

Annika Reinke, Minu D. Tizabi, Michael Baumgartner et al.

2023 · 20 Zit.

Biomedical image analysis competitions: The state of current participation practice

Matthias Eisenmann, Annika Reinke, Vivienn Weru et al.

2022 · 17 Zit.

Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood tests

Baker Nawfal Jawad, Shakir Maytham Shaker, Izzet Altintas et al.

2024 · 14 Zit.

Artificial Intelligence and Privacy

Mateusz Jurewicz, Natacha Klein Käfer, Esben Kran

2024 · 11 Zit.

Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI?

Evangelia Christodoulou, Annika Reinke, Rola Houhou et al.

2024 · 9 Zit.

Revealing Neural Network Bias to Non-Experts Through Interactive Counterfactual Examples

Chelsea M. Myers, Evan Freed, Luis Fernando Laris Pardo et al.

2020 · 8 Zit.

Empower Diversity in AI Development

Karl Werder, Lan Cao, Balasubramaniam Ramesh et al.

2024 · 7 Zit.