Webinar

Datasets through the Lđź‘€king-Glass

Datasets through the Lđź‘€king-Glass is a webinar series focusing on the data aspects on 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.

All previous talks where the authors have agreed to share the talk, can be found in our YouTube playlist.

Next webinar: TBA

Date: TBA

Where: Zoom:

Speakers: TBA

Previous talks:

All previous abstracts can be found here.

  • S01E01 - Dr. Roxana Daneshjou (Stanford University School of Medicine, Stanford, CA, USA). 27th Feb 2023. Challenges with equipoise and fairness in AI/ML datasets in dermatology
  • S01E02 - Dr. David Wen (Oxford University Clinical Academic Graduate School, University of Oxford, Oxford, UK). 27th Feb 2023. Characteristics of open access skin cancer image datasets: implications for equitable digital health
  • S01E03 - Prof. Colin Fleming (Ninewells Hospital, Dundee, UK). 27th Feb 2023. Characteristics of skin lesions datasets
  • S02E01 - Prof. Amber Simpson (Queen’s University, Canada). 5th June 2023. The medical segmentation decathlon
  • S02E02 - Dr. Esther E. Bron (Erasmus MC - University Medical Center Rotterdam, the Netherlands). 5th June 2023. Image analysis and machine learning competitions in dementia
  • S02E03 - Dr. Ujjwal Baid (University of Pennsylvania, USA). 5th June 2023. Brain tumor segmentation challenge 2023
  • S03E01 - Dr. Thijs Kooi (Lunit, South Korea). 18th September 2023. Optimizing annotation cost for AI based medical image analysis
  • S03E02 - Dr. Andre Pacheco (Federal University of EspĂ­rito Santo, Brazil). 18th September 2023. PAD-UFES-20: the challenges and opportunities in creating a skin lesion dataset
  • S04E01 - Dr. Jessica Schrouff (Google DeepMind, UK). 4th December 2023. Detecting shortcut learning for fair medical AI
  • S04E02 - Rhys Compton and Lily Zhang (New York University, USA). 4th December 2023. When more is less: Incorporating additional datasets can hurt performance by introducing spurious correlations
  • S04E03 - Dr. Enzo Ferrante (CONICET, Argentina). 4th December 2023. Building and auditing a large-scale x-ray segmentation dataset with automatic annotations: Navigating fairness without ground-truth
  • S05E01 - Hubert Dariusz ZajÄ…c and Natalia-Rozalia Avlona (University of Copenhagen, Denmark). 25th March 2024. Ground Truth Or Dare: Factors Affecting The Creation Of Medical Datasets For Training AI
  • S05E02 - Dr. Annika Reinke (DKFZ, Germany). 25th March 2024. Why your Dataset Matters: Choosing the Right Metrics for Biomedical Image Analysis
  • S05E03 - Alceu Bissoto and Dr. Sandra Avila (UNICAMP, Brazil). 25th March 2024. The Performance of Transferability Metrics does not Translate to Medical Tasks
  • S06E01 - Hava Chaptoukaev and Maria Zuluaga (EURECOM, France). 24th February 2025. Acquiring, curating and releasing a multi-modal dataset for stress detection: ambitions, achievements, mistakes and lessons learned
  • S06E02 - Alice Jin (Massachusetts Institute of Technology, USA). 24th February 2025. Fair Multimodal Checklists for Interpretable Clinical Time Series Prediction
  • S06E03 - Malih Alikhani and Resmi Ramachandranpillai (Northeastern University, USA). 24th February 2025. Towards Equity: Overcoming Fairness Challenges in Multimodal Learning
  • S07E01 - Amelia JimĂ©nez-Sánchez (IT University of Copenhagen, Denmark). 12th May 2025. In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review
  • S07E02 - Tiarna Lee (King’s College London, UK). 12th May 2025. Racial bias in cardiac imaging
  • S07E03 - Dewinda J. Rumala (UNIVERSA AI, Switzerland). 12th May 2025. Seeing the Same Brain Twice: Data Leakage and Identity Bias in Brain MRI Analysis
  • S08E01 - Mamunur Rahaman (University of New South Wales, Australia). 20th October 2025. Advancing Computational Pathology: Multimodal Datasets and Deep Learning Insights
  • S08E02 - David Restrepo (CentraleSupĂ©lec, UniversitĂ© Paris-Saclay, France). 20th October 2025. Opening Eyes: Advancing Equitable AI Through Open Ophthalmology Data
  • S08E03 - Yuki Arase (School of Computing, Institute of Science Tokyo, Japan). 20th October 2025. Japanese Medical Text Simplification Using Patient Blogs
  • S09E01 - Evangelia Christodoulou (German Cancer Research Center (DKFZ), Germany). 2nd March 2026. From Metrics to Meaning: Making Evaluation Matter in Medical Imaging AI
  • S09E02 - Abhishek Singh Sambyal (University of Oulu, Finland). 2nd March 2026. Beyond Accuracy: Understanding Calibration in Medical Image Classification
  • S09E03 - Raghavendra Selvan (University of Copenhagen, Denmark). 2nd March 2026. Carbon footprint of Medical Image Analysis and Mitigation Strategies
  • S10E01 - Laura Quinn (University of Birmingham, UK). 22nd October 2026. Interobserver Variability in Breast Screening: A Comparison of Measures
  • S10E02 - Kumar Abhishek (Simon Fraser University’s Medical Image Analysis Lab, Canada). 22nd October 2026. Styles, Signals, and Scale: Learning from Annotator Disagreement in Skin Lesion Segmentation
  • S10E03 - Leo Joskowicz (Hebrew University of Jerusalem, Israel). 22nd October 2026. Observer variability in the AI machine learning zoo

All previous abstracts can be found here.

Organizers

Amelia Jiménez-Sánchez at the Universitat de Barcelona (Spain), Théo Sourget & Veronika Cheplygina at the IT University of Copenhagen (Denmark), and Steff Groefsema at the University of Groningen (the Netherlands) and Carlos Aumente-Maestro at the German Cancer Research Center and Helmholtz Imaging (Germany). This project has received funding from the Independent Research Fund Denmark - Inge Lehmann number 1134-00017B.

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