Datasets through the Lđź‘€king-Glass
About
We are focusing on the data aspects of learning-based methods. Our aim is to build a community of scientists interested in understanding how the data we use affects the algorithms and society as a whole, instead of only optimizing for a performance metric. We draw inspiration from a variety of topics, such as data curation to build datasets, meta-data, shortcuts, fairness, ethics and philosophy in AI.
The best way to get a sense of our topics of interest is to look at our webinar series and the publications discussed during our workshop.
News
| Jan 31, 2025 | After our in-person workshop, we have written a joint paper In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review. We propose a living review that continuously tracks public datasets and their associated research artifacts across multiple medical imaging applications. |
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| Sep 19, 2024 | We had the first edition of our workshop “In the Picture: Medical Imaging Datasets” at Nyborg Strand Hotel (Denmark)! It was focused on challenges within medical imaging datasets that hinder the development of fair and robust AI algorithms. Check the presentations’ slides and videos |
| Mar 25, 2024 | We had the fifth edition of our webinar! This edition was focused on dataset construction and metrics with talk from Hubert Dariusz ZajÄ…c and Natalia-Rozalia Avlona, Dr. Annika Reinke and Alceu Bissoto and Dr. Sandra Avila. |
| Dec 04, 2023 | We had the forth edition of our webinar! This edition was focused on shortcuts and biases with talk from Dr. Enzo Ferrante, Rhys Compton and Lily Zhang. |
| Sep 18, 2023 | We had the third edition of our webinar! This edition was focused on rethinking annotations with talk from Dr. Thijs Kooi and Dr. Andre Pacheco. |
| Jun 05, 2023 | We had the second edition of our webinar! This edition was focused on datasets from medical image challenges with talk from Prof. Amber Simpson, Prof. Esther E. Bron and Prof. Spyridon Bakas. |
| Feb 27, 2023 | We had the first edition of our webinar! This edition was focused on skin lesions datasets with talk from Dr. Roxana Daneshjou, Dr. David Wen and Prof. dr. Colin Fleming. |
Selected publications
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arXiv preprint arXiv:2501.10727, 2025 -
arXiv preprint arXiv:2407.17596, 2024 -
In The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track , 2024 -
arXiv preprint arXiv:2403.04484, 2024 -
In Medical Imaging with Deep Learning , 2024 -
Journal of the American College of Radiology, 2023 -
arXiv preprint arXiv:2312.14223, 2023 -
In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society , 2023
