PURRlab @ IT University of Copenhagen

Pattern Recognition Revisited


PURRLab research interests lie within the broad area of trustworthy machine learning and its applications to medical imaging with a focus on datasets. We are particularly interested in understanding the similarity and diversity of datasets, methods for learning with limited labeled data such as transfer learning, and meta-research on machine learning in medical imaging.

The best way to get a sense of what’s currently going on in the lab is to read about our people and projects.

PURRLab is a part of DASYA research group in the department of Computer Science at the IT University of Copenhagen and is led by Veronika Cheplygina.

PURRLab research is being supported by the Dutch Research Council, Novo Nordisk Foundation and the Independent Research Council of Denmark.


Jun 7, 2023 Presentations at Health Data Science Day
Apr 18, 2023 Paper on shortcuts at ISBI2023
Feb 27, 2023 Théo Sourget from University of Rouen visits us from February 27th to March 31st.
Aug 1, 2022 Amelia joins the lab! :sparkles: :smile:
Jan 1, 2022 Bethany and Dovile join PURRlab!
Feb 1, 2021 PURRlab moves to ITU Copenhagen, Denmark!

Selected publications

  1. Machine learning for medical imaging: methodological failures and recommendations for the future
    Gaël Varoquaux, and Veronika Cheplygina
    NPJ Digital Medicine 2022
  2. ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification
    Ralf Raumanns, Gerard Schouten, Max Joosten, Josien PW Pluim, and Veronika Cheplygina
    arXiv preprint arXiv:2107.12734 2021
  3. Detecting Shortcuts in Medical Images – A Case Study in Chest X-rays
    Amelia Jiménez-Sånchez, Dovile Juodelyte, Bethany Chamberlain, and Veronika Cheplygina
  4. Cats or CAT scans: Transfer learning from natural or medical image source data sets?
    Current Opinion in Biomedical Engineering 2019