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.
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!|
|Jan 1, 2022||Bethany and Dovile join PURRlab!|
|Feb 1, 2021||PURRlab moves to ITU Copenhagen, Denmark!|
- Machine learning for medical imaging: methodological failures and recommendations for the futureNPJ Digital Medicine 2022
- ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classificationarXiv preprint arXiv:2107.12734 2021
- Detecting Shortcuts in Medical Images – A Case Study in Chest X-rays2022
- Cats or CAT scans: Transfer learning from natural or medical image source data sets?Current Opinion in Biomedical Engineering 2019