1. Revisiting Hidden Representations in Transfer Learning for Medical Imaging
    Transactions on Machine Learning Research 2023
  2. Augmenting Chest X-ray Datasets with Non-Expert Annotations
    Cathrine Damgaard, Trine Naja Eriksen, Dovile Juodelyte, Veronika Cheplygina, and Amelia Jiménez-Sánchez
    arXiv preprint arXiv:2309.02244 2023


  1. Machine learning for medical imaging: methodological failures and recommendations for the future
    Ga√ęl Varoquaux,¬†and¬†Veronika Cheplygina
    NPJ Digital Medicine 2022
  2. Detection of Furigana Text in Images
    Nikolaj Kj√łller Bjerregaard,¬†Veronika Cheplygina,¬†and¬†Stefan Heinrich
    arXiv preprint arXiv:2207.03960 2022
  3. Predicting Bearings’ Degradation Stages for Predictive Maintenance in the Pharmaceutical Industry
    Dovile Juodelyte, Veronika Cheplygina, Therese Graversen, and Philippe Bonnet
    arXiv preprint arXiv:2203.03259 2022
  4. Memory-aware curriculum federated learning for breast cancer classification
    Amelia Jiménez-Sánchez, Mickael Tardy, Miguel A González Ballester, Diana Mateus, and Gemma Piella
    Computer Methods and Programs in Biomedicine 2022
  5. Detecting Shortcuts in Medical Images ‚Äď A Case Study in Chest X-rays
    Amelia Jiménez-Sánchez, Dovile Juodelyte, Bethany Chamberlain, and Veronika Cheplygina


  1. 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
  2. Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classification
    Irma van den Brandt, Floris Fok, Bas Mulders, Joaquin Vanschoren, and Veronika Cheplygina
    arXiv preprint arXiv:2107.05940 2021
  3. High-level prior-based loss functions for medical image segmentation: A survey
    Rosana El Jurdi, Caroline Petitjean, Paul Honeine, Veronika Cheplygina, and Fahed Abdallah
    Computer Vision and Image Understanding 2021
  4. Crowdsourcing airway annotations in chest computed tomography images
    Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, Harm AWM Tiddens, and Marleen Bruijne
    PLoS ONE 2021


  1. Primary Tumor Origin Classification of Lung Nodules in Spectral CT using Transfer Learning
    Linde S Hesse, Pim A Jong, Josien PW Pluim, and Veronika Cheplygina
    arXiv preprint arXiv:2006.16633 2020
  2. Predicting Scores of Medical Imaging Segmentation Methods with Meta-Learning
    Tom Sonsbeek, and Veronika Cheplygina
    In Interpretable and Annotation-Efficient Learning for Medical Image Computing (MICCAI LABELS) 2020
  3. Risk of Training Diagnostic Algorithms on Data with Demographic Bias
    Samaneh Abbasi-Sureshjani, Ralf Raumanns, Britt EJ Michels, Gerard Schouten, and Veronika Cheplygina
    In Interpretable and Annotation-Efficient Learning for Medical Image Computing (MICCAI LABELS) 2020


  1. A survey of crowdsourcing in medical image analysis
    Silas √ėrting,¬†Andrew Doyle,¬†Arno Hilten,¬†Matthias Hirth,¬†Oana Inel, and 4 more authors
    Human Computation Journal 2019
  2. Cats or CAT scans: Transfer learning from natural or medical image source data sets?
    Current Opinion in Biomedical Engineering 2019
  3. Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
    Veronika Cheplygina, Marleen Bruijne, and Josien PW Pluim
    Medical Image Analysis 2019


  1. Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images
    Isabel Pino Pena, Veronika Cheplygina, Sofia Paschaloudi, Morten Vuust, Jesper Carl, and 3 more authors
    PLoS ONE 2018
  2. Crowd disagreement about medical images is informative
    Veronika Cheplygina, and Josien P W Pluim
    In Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (MICCAI LABELS) 2018
  3. Multiple Instance Learning: A Survey of Problem Characteristics and Applications
    M.-A. Carbonneau, V. Cheplygina, E. Granger, and G. Gagnon
    Pattern Recognition 2018
  4. Transfer learning for multi-center classification of chronic obstructive pulmonary disease
    Veronika Cheplygina,¬†Isabel Pino Pe√Īa,¬†Jesper Holst Pedersen,¬†David A Lynch,¬†Lauge S√łrensen, and 1 more author
    IEEE Journal of Biomedical and Health Informatics 2018


  1. Exploring the similarity of medical imaging classification problems
    Veronika Cheplygina, Pim Moeskops, Mitko Veta, Behdad Dasht Bozorg, and Josien Pluim
    In Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (MICCAI LABELS) 2017


  1. Dissimilarity-based ensembles for multiple instance learning
    Veronika Cheplygina, David M. J. Tax, and Marco Loog
    IEEE Transactions on Neural Networks and Learning Systems 2016


  1. Characterizing Multiple Instance Datasets
    Veronika Cheplygina, and David M J Tax
    In Similarity-Based Pattern Recognition 2015
  2. On classification with bags, groups and sets
    Veronika Cheplygina, David M J Tax, and Marco Loog
    Pattern Recognition Letters 2015
  3. Label stability in multiple instance learning
    V. Cheplygina,¬†L. S√łrensen,¬†D. M. J. Tax,¬†M. Bruijne,¬†and¬†M. Loog
    In Medical Imaging Computing and Computer Assisted Intervention (MICCAI) 2015
  4. Multiple instance learning with bag dissimilarities
    Veronika Cheplygina, David M. J. Tax, and Marco Loog
    Pattern Recognition 2015