S. Jarkman, M. Karlberg, M. Poceviciute, A. Boden, P. Bandi, G. Litjens, C. Lundstrom, 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. Polonia, 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.
N. Marini, S. Marchesin, S. Otalora, 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.
J. Ogony, T. de Bel, D. Radisky, J. Kachergus, E. Thompson, A. Degnim, K. Ruddy, T. Hilton, M. Stallings-Mann, C. Vachon, T. Hoskin, M. Heckman, R. Vierkant, L. White, R. Moore, J. Carter, M. Jensen, L. Pacheco-Spann, J. Henry, A. Storniolo, S. Winham, J. van der Laak and M. Sherman, "Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence",
Breast Cancer Research,
2022;24.
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.
M. Sherman, T. de Bel, M. Heckman, L. White, J. Ogony, M. Stallings-Mann, T. Hilton, A. Degnim, R. Vierkant, T. Hoskin, M. Jensen, L. Pacheco-Spann, J. Henry, A. Storniolo, J. Carter, S. Winham, D. Radisky and J. van der Laak, "Serum hormone levels and normal breast histology among premenopausal women",
Breast Cancer Research and Treatment,
2022;194:149-158.
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.
A. van der Kamp, T. Waterlander, T. de Bel, J. van der Laak, M. van den Heuvel-Eibrink, A. Mavinkurve-Groothuis and R. de Krijger, "Artificial Intelligence in Pediatric Pathology: The Extinction of a Medical Profession or the Key to a Bright Future?",
Pediatric and Developmental Pathology,
2022;25:380-387.
B. Sturm, D. Creytens, J. Smits, A. Ooms, E. Eijken, E. Kurpershoek, H. Küsters-Vandevelde, C. Wauters, W. Blokx and J. van der Laak, "Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm",
Diagnostics,
2022;12:436.
T. de Bel, G. Litjens, J. Ogony, M. Stallings-Mann, J. Carter, T. Hilton, D. Radisky, R. Vierkant, B. Broderick, T. Hoskin, S. Winham, M. Frost, D. Visscher, T. Allers, A. Degnim, M. Sherman and J. van der Laak, "Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning",
npj Breast Cancer,
2022;8.
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.
L. Miesen, P. Bándi, B. Willemsen, F. Mooren, T. Strieder, E. Boldrini, V. Drenic, J. Eymael, R. Wetzels, J. Lotz, N. Weiss, E. Steenbergen, T. van Kuppevelt, M. van Erp, J. van der Laak, N. Endlich, M. Moeller, J. Wetzels, J. Jansen and B. Smeets, "Parietal epithelial cells maintain the epithelial cell continuum forming Bowman's space in focal segmental glomerulosclerosis",
Disease Models & Mechanisms,
2022;15.
J. van der Laak, K. Grünberg, A. Frisk and P. Moulin, "BUILDING AN E.U.-SCALE DIGITAL PATHOLOGY REPOSITORY: THE BIGPICTURE INITIATIVE",
Journal of Pathology Informatics,
2022;13:100026.
M. van Bommel, J. Bogaerts, R. Hermens, M. Steenbeek, J. de Hullu, J. van der Laak and M. Simons, "2022-RA-646-ESGO Consensus based recommendations for the diagnosis of serous tubal intraepithelial carcinoma, an international delphi study",
Pathology,
2022.
L. van Eekelen, E. Munari, I. Girolami, A. Eccher, J. van der Laak, K. Grunberg, 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.