C. Grisi, K. Faryna, N. Uysal, V. Agosti, E. Munari, S. Kammerer-Jacquet, P. Salles, Y. Tolkach, R. Büttner, S. Semko, M. Pikul, A. Heidenreich, J. van der Laak and G. Litjens, "Deep Learning From Routine Histology Improves Risk Stratification for Biochemical Recurrence in Prostate Cancer",
arXiv:2603.14187,
2026.
K. Faryna, L. Tessier, J. Retamero, S. Bonthu, P. Samanta, N. Singhal, S. Kammerer-Jacquet, C. Radulescu, V. Agosti, A. Collin, X. Farre', J. Fontugne, R. Grobholz, A. Hoogland, K. Leite, M. Oktay, A. Polonia, P. Roy, P. Salles, T. van der Kwast, J. van Ipenburg, J. van der Laak and G. Litjens, "Evaluation of AI-based Gleason grading algorithms "in the wild"",
Modern Pathology,
2024:100563.
K. Faryna, J. van der Laak and G. Litjens, "Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology",
Computers in Biology and Medicine,
2024;170:108018.
K. Faryna, J. van der Laak and G. Litjens, "Towards embedding stain-invariance in convolutional neural networks for H&E-stained histopathology",
Medical Imaging 2024: Digital and Computational Pathology,
2024.
K. Faryna, J. van der Laak and G. Litjens, "Tailoring automated data augmentation to H&E-stained histopathology",
Medical Imaging with Deep Learning,
2021.
A. Saha, F. Tushar, K. Faryna, V. D'Anniballe, R. Hou, M. Mazurowski, G. Rubin and J. Lo, "Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features",
Medical Imaging,
2020;11314:39 - 44.
K. Faryna, F. Tushar, V. D'Anniballe, R. Hou, G. Rubin and J. Lo, "Attention-guided classification of abnormalities in semi-structured computed tomography reports",
Medical Imaging,
2020;11314:397 - 403.
K. Faryna, K. Koschmieder, M. Paul, T. van den Heuvel, A. van der Eerden, R. Manniesing and B. van Ginneken, "Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation",
Medical Imaging Meets NeurIPS Workshop - 34th Conference on Neural Information Processing Systems (NeurIPS),
2020.