S. Sun, L. Tessier, F. Meeuwsen, C. Grisi, D. van Midden, G. Litjens and C. Baumgartner, "Label-free Concept Based Multiple Instance Learning for Gigapixel Histopathology",
arXiv:2501.02922,
2025.
M. van Rijthoven, W. Aswolinskiy, L. Tessier, M. Balkenhol, J. Bogaerts, D. Drubay, L. Blesa, D. Peeters, E. Stovgaard, A. L\aenkholm , H. Haynes, L. Craciun, D. Larsimont, M. Amgad, L. Cooper, C. de Kock, V. Dechering, J. Lotz, N. Weiss, M. van Bockstal, C. Galant, E. Lips, H. Horlings, J. Wesseling, L. Mulder, S. van den Belt, K. Weber, P. Jank, C. Denkert, E. Munari, G. Bogina, C. Russ, A. Lemm, S. Loi, J. Douglas, S. Michiels, H. Joensuu, M. Fan, D. Lee, J. Ye, K. Byun, J. Kim, S. Xu, Z. Ji, F. Xie, J. Kuang, X. Chen, L. Chen, A. Tsakiroglou, R. Byers, M. Fergie, V. Ramanathan, A. Martel, A. Shephard, S. Ahmed Raza, M. Jahanifar, N. Rajpoot, S. Cho, D. Kim, H. Jang, C. Park, K. Kim, R. Donders, S. Maurits, M. Groeneveld, A. Mickan, J. Meakin, B. van Ginneken, R. Salgado, J. van der Laak and F. Ciompi, "Tumor-infiltrating lymphocytes in breast cancer through artificial intelligence: biomarker analysis from the results of the TIGER challenge",
medRxiv,
2025.
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.
L. Tessier, C. Gonzalez-Gonzalo, D. Tellez, W. Bulten and M. van der Laak, "Large-scale validation of AI-assisted mitosis counting in breast cancer",
European Congress on Digital Pathology,
2024.
W. Aswolinskiy, E. Munari, H. Horlings, L. Mulder, G. Bogina, J. Sanders, Y. Liu, A. van den Belt-Dusebout, L. Tessier, M. Balkenhol, M. Stegeman, J. Hoven, J. Wesseling, J. van der Laak, E. Lips and F. Ciompi, "PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning",
Breast Cancer Research,
2023;25.
J. Spronck, T. Gelton, L. van Eekelen, J. Bogaerts, L. Tessier, M. van Rijthoven, L. van der Woude, M. van den Heuvel, W. Theelen, J. van der Laak and F. Ciompi, "nnUNet meets pathology: bridging the gap for application to whole-slide images and computational biomarkers",
Medical Imaging with Deep Learning,
2023.
J. Spronck, L. Eekelen, L. Tessier, J. Bogaerts, L. van der Woude, M. van den Heuvel, W. Theelen and F. Ciompi, "Deep learning-based quantification of immune infiltrate for predicting response to pembrolizumab from pre-treatment biopsies of metastatic non-small cell lung cancer: A study on the PEMBRO-RT phase II trial",
Immuno-Oncology and Technology,
2022.