M. Aubreville, N. Stathonikos, C. Bertram, R. Klopfleisch, N. Ter Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T. Donovan, A. Maier, J. Breen, N. Ravikumar, Y. Chung, J. Park, R. Nateghi, F. Pourakpour, R. Fick, S. Ben Hadj, M. Jahanifar, A. Shephard, J. Dexl, T. Wittenberg, S. Kondo, M. Lafarge, V. Koelzer, J. Liang, Y. Wang, X. Long, J. Liu, S. Razavi, A. Khademi, S. Yang, X. Wang, R. Erber, A. Klang, K. Lipnik, P. Bolfa, M. Dark, G. Wasinger, M. Veta and K. Breininger, "Mitosis domain generalization in histopathology images - The MIDOG challenge.",
Medical Image Analysis,
2022;84:102699.
L. Adams, M. Makowski, G. Engel, M. Rattunde, F. Busch, P. Asbach, S. Niehues, S. Vinayahalingam, B. van Ginneken, G. Litjens and K. Bressem, "Dataset of prostate MRI annotated for anatomical zones and cancer.",
Data in brief,
2022;45:108739.
S. Jarkman, M. Karlberg, M. Pocevičiūtė, A. Bodén, P. Bándi, G. Litjens, C. Lundström, D. Treanor and J. van der Laak, "Generalization of Deep Learning in Digital Pathology: Experience in Breast Cancer Metastasis Detection.",
Cancers,
2022;14(21).
C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polónia, H. Horlings, W. Weichert, J. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J. Bokhorst, J. van der Laak and F. Ciompi, "Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer.",
NPJ breast cancer,
2022;8(1):120.
S. Marchesin, F. Giachelle, N. Marini, M. Atzori, S. Boytcheva, G. Buttafuoco, F. Ciompi, G. Di Nunzio, F. Fraggetta, O. Irrera, H. Müller, T. Primov, S. Vatrano and G. Silvello, "Empowering digital pathology applications through explainable knowledge extraction tools.",
Journal of pathology informatics,
2022;13:100139.
E. Munari, G. Querzoli, M. Brunelli, M. Marconi, M. Sommaggio, M. Cocchi, G. Martignoni, G. Netto, A. Caliò, L. Quatrini, F. Mariotti, C. Luchini, I. Girolami, A. Eccher, D. Segala, F. Ciompi, G. Zamboni, L. Moretta and G. Bogina, "Comparison of three validated PD-L1 immunohistochemical assays in urothelial carcinoma of the bladder: interchangeability and issues related to patient selection.",
Frontiers in immunology,
2022;13:954910.
N. Marini, S. Marchesin, S. Otálora, M. Wodzinski, A. Caputo, M. van Rijthoven, W. Aswolinskiy, J. Bokhorst, D. Podareanu, E. Petters, S. Boytcheva, G. Buttafuoco, S. Vatrano, F. Fraggetta, J. van der Laak, M. Agosti, F. Ciompi, G. Silvello, H. Muller and M. Atzori, "Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.",
NPJ digital medicine,
2022;5(1):102.
M. Hermsen, F. Ciompi, A. Adefidipe, A. Denic, A. Dendooven, B. Smith, D. van Midden, J. Brasen, J. Kers, M. Stegall, P. Bándi, T. Nguyen, Z. Swiderska-Chadaj, B. Smeets, L. Hilbrands and J. van der Laak, "Convolutional neural networks for the evaluation of chronic and inflammatory lesions in kidney transplant biopsies",
American Journal of Pathology,
2022;192(10):1418-1432.
L. Adams, M. Makowski, G. Engel, M. Rattunde, F. Busch, P. Asbach, S. Niehues, S. Vinayahalingam, B. van Ginneken, G. Litjens and K. Bressem, "Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection.",
Computers in biology and medicine,
2022;148:105817.
M. Antonelli, A. Reinke, S. Bakas, K. Farahani, A. Kopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, B. van Ginneken, M. Bilello, P. Bilic, P. Christ, R. Do, M. Gollub, S. Heckers, H. Huisman, W. Jarnagin, M. McHugo, S. Napel, J. Pernicka, K. Rhode, C. Tobon-Gomez, E. Vorontsov, J. Meakin, S. Ourselin, M. Wiesenfarth, P. Arbelaez, B. Bae, S. Chen, L. Daza, J. Feng, B. He, F. Isensee, Y. Ji, F. Jia, I. Kim, K. Maier-Hein, D. Merhof, A. Pai, B. Park, M. Perslev, R. Rezaiifar, O. Rippel, I. Sarasua, W. Shen, J. Son, C. Wachinger, L. Wang, Y. Wang, Y. Xia, D. Xu, Z. Xu, Y. Zheng, A. Simpson, L. Maier-Hein and M. Cardoso, "The Medical Segmentation Decathlon",
Nature Communications,
2022;13(1):4128.
H. Pinckaers, J. van Ipenburg, J. Melamed, A. De Marzo, E. Platz, B. van Ginneken, J. van der Laak and G. Litjens, "Predicting biochemical recurrence of prostate cancer with artificial intelligence",
Communications Medicine,
2022;2:64.
I. Girolami, L. Pantanowitz, S. Marletta, M. Hermsen, J. van der Laak, E. Munari, L. Furian, F. Vistoli, G. Zaza, M. Cardillo, L. Gesualdo, G. Gambaro and A. Eccher, "Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review.",
Journal of nephrology,
2022.
S. Satturwar, I. Girolami, E. Munari, F. Ciompi, A. Eccher and L. Pantanowitz, "Program death ligand-1 immunocytochemistry in lung cancer cytological samples: A systematic review.",
Diagnostic cytopathology,
2022;50(6):313-323.
W. Bulten, K. Kartasalo, P. Chen, P. Strom, H. Pinckaers, K. Nagpal, Y. Cai, D. Steiner, H. van Boven, R. Vink, C. de Hulsbergen-van Kaa, J. van der Laak, M. Amin, A. Evans, T. van der Kwast, R. Allan, P. Humphrey, H. Gronberg, H. Samaratunga, B. Delahunt, T. Tsuzuki, T. Hakkinen, L. Egevad, M. Demkin, S. Dane, F. Tan, M. Valkonen, G. Corrado, L. Peng, C. Mermel, P. Ruusuvuori, G. Litjens, M. Eklund, A. Brilhante, A. Cakir, X. Farre, K. Geronatsiou, V. Molinie, G. Pereira, P. Roy, G. Saile, P. Salles, E. Schaafsma, J. Tschui, J. Billoch-Lima, E. Pereira, M. Zhou, S. He, S. Song, Q. Sun, H. Yoshihara, T. Yamaguchi, K. Ono, T. Shen, J. Ji, A. Roussel, K. Zhou, T. Chai, N. Weng, D. Grechka, M. Shugaev, R. Kiminya, V. Kovalev, D. Voynov, V. Malyshev, E. Lapo, M. Campos, N. Ota, S. Yamaoka, Y. Fujimoto, K. Yoshioka, J. Juvonen, M. Tukiainen, A. Karlsson, R. Guo, C. Hsieh, I. Zubarev, H. Bukhar, W. Li, J. Li, W. Speier, C. Arnold, K. Kim, B. Bae, Y. Kim, H. Lee, J. Park and the PANDA challenge consortium, "Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge",
Nature Medicine,
2022.
M. Schuurmans, N. Alvás, P. Vendittelli, H. Huisman and J. Hermans, "Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging",
Cancers,
2022:3498.
M. D'Amato, P. Szostak and B. Torben-Nielsen, "A Comparison Between Single- and Multi-Scale Approaches for Classification of Histopathology Images",
Frontiers in Public Health,
2022;10.
L. Studer, J. Bokhorst, F. Ciompi, A. Fischer and H. Dawson, "Building-T-cell score is a potential predictor for more aggressive treatment in pT1 colorectal cancers",
Proceedings of the ECDP 2022 18th European Congress on Digital Pathology,
2022.
E. Chelebian and F. Ciompi, "Seeded iterative clustering for histology region identification",
Learning Meaningful Representations of Life, NeurIPS 2022,
2022.
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.
E. van Genugten, B. Piet, G. Schreibelt, T. van Oorschot, G. van den Heuvel, F. Ciompi, C. Jacobs, J. de Vries, M. van den Heuvel and E. Aarntzen, "Imaging tumor-infiltrating CD8 (+) T-cells in non-small cell lung cancer patients upon neo-adjuvant treatment with durvalumab",
European Molecular Imaging Meeting,
2022.
L. van Eekelen, E. Munari, I. Girolami, A. Eccher, J. van der Laak, K. Grünberg, M. Looijen-Salamon, S. Vos and F. Ciompi, "Inter-rater agreement of pathologists on determining PD-L1 status in non-small cell lung cancer",
European Congress of Pathology,
2022.
L. van Eekelen, E. Munari, L. Meesters, G. de Souza, M. Demirel-Andishmand, D. Zegers, M. Looijen-Salamon, S. Vos and F. Ciompi, "Nuclei detection with YOLOv5 in PD-L1 stained non-small cell lung cancer whole slide images",
European Congress of Pathology,
2022.