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.
N. Brouwer, A. Khan, J. Bokhorst, F. Ayatollahi, J. Hay, F. Ciompi, F. Simmer, N. Hugen, J. de Wilt, M. Berger, A. Lugli, I. Zlobec, J. Edwards and I. Nagtegaal, "The complexity of shapes; how the circularity of tumor nodules impacts prognosis in colorectal cancer",
Modern Pathology,
2023:100376.
Y. Jiao, J. van der Laak, S. Albarqouni, Z. Li, T. Tan, A. Bhalerao, J. Ma, J. Sun, J. Pocock, J. Pluim, N. Koohbanani, R. Bashir, S. Raza, S. Liu, S. Graham, S. Wetstein, S. Khurram, T. Watson, N. Rajpoot, M. Veta and F. Ciompi, "LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset",
IEEE Journal of Biomedical and Health Informatics,
2023:1-12.
J. Bokhorst, I. Nagtegaal, F. Fraggetta, S. Vatrano, W. Mesker, M. Vieth, J. van der Laak and F. Ciompi, "Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images",
Scientific Reports,
2023;13:8398.
J. Bokhorst, I. Nagtegaal, I. Zlobec, H. Dawson, K. Sheahan, F. Simmer, R. Kirsch, M. Vieth, A. Lugli, J. van der Laak and F. Ciompi, "Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer",
Cancers,
2023;15(7):2079.
L. Menotti, G. Silvello, M. Atzori, S. Boytcheva, F. Ciompi, G. Di Nunzio, F. Fraggetta, F. Giachelle, O. Irrera, S. Marchesin, N. Marini, H. Müller and T. Primov, "Modelling digital health data: The ExaMode ontology for computational pathology",
Journal of Pathology Informatics,
2023;14:100332.
M. Smit, F. Ciompi, J. Bokhorst, G. van Pelt, O. Geessink, H. Putter, R. Tollenaar, J. van Krieken, W. Mesker and J. van der Laak, "Deep learning based tumor-stroma ratio scoring in colon cancer correlates with microscopic assessment",
Journal of Pathology Informatics,
2023.
D. Page, G. Broeckx, C. Jahangir, S. Verbandt, R. Gupta, J. Thagaard, R. Khiroya, Z. Kos, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. Almeida, I. Alvarado-Cabrero, F. Azmoudeh-Ardalan, S. Badve, N. Baharun, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, N. Bouchmaa, O. Burgues, M. Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, F. Dantas Portela, F. Deman, S. Demaria, S. Dudgeon, M. Elghazawy, S. Ely, C. Fernandez-Martín, S. Fineberg, S. Fox, W. Gallagher, J. Giltnane, S. Gnjatic, P. Gonzalez-Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, A. Hardas, S. Hart, J. Hartman, S. Hewitt, A. Hida, H. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. Janssen, M. Kahila, T. Kataoka, K. Kawaguchi, D. Kharidehal, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang-Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, F. Minhas, S. Mittal, D. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault-Llorca, R. Perera, C. Pinard, J. Pinto-Cardenas, G. Pruneri, L. Pusztai, A. Rahman, N. Rajpoot, B. Rapoport, T. Rau, J. Reis-Filho, J. Ribeiro, D. Rimm, A. Vincent-Salomon, M. Salto-Tellez, J. Saltz, S. Sayed, K. Siziopikou, C. Sotiriou, A. Stenzinger, M. Sughayer, D. Sur, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. Thompson, T. Tramm, W. Tran, J. van der Laak, P. van Diest, G. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado and E. Specht Stovgaard, "Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer",
The Journal of Pathology,
2023;260:514-532.
J. Thagaard, G. Broeckx, D. Page, C. Jahangir, S. Verbandt, Z. Kos, R. Gupta, R. Khiroya, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. Almeida, I. Alvarado-Cabrero, M. Amgad, F. Azmoudeh-Ardalan, S. Badve, N. Baharun, E. Balslev, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, N. Bouchmaa, O. Burgues, A. Chardas, M. U Chon Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, A. Dahl, F. Dantas Portela, F. Deman, S. Demaria, J. Doré Hansen, S. Dudgeon, T. Ebstrup, M. Elghazawy, C. Fernandez-Martín, S. Fox, W. Gallagher, J. Giltnane, S. Gnjatic, P. Gonzalez-Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, S. Hart, J. Hartman, S. Hauberg, S. Hewitt, A. Hida, H. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. Janssen, M. Kahila, T. Kataoka, K. Kawaguchi, D. Kharidehal, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang-Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, F. Minhas, S. Mittal, D. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault-Llorca, R. Perera, C. Pinard, J. Pinto-Cardenas, G. Pruneri, L. Pusztai, A. Rahman, N. Rajpoot, B. Rapoport, T. Rau, J. Reis-Filho, J. Ribeiro, D. Rimm, A. Roslind, A. Vincent-Salomon, M. Salto-Tellez, J. Saltz, S. Sayed, E. Scott, K. Siziopikou, C. Sotiriou, A. Stenzinger, M. Sughayer, D. Sur, S. Fineberg, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. Thompson, T. Tramm, W. Tran, J. van der Laak, P. van Diest, G. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, R. Zin, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado and E. Specht Stovgaard, "Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer",
The Journal of Pathology,
2023;260:498-513.
J. Bokhorst, F. Ciompi, S. Öztürk, A. Oguz Erdogan, M. Vieth, H. Dawson, R. Kirsch, F. Simmer, K. Sheahan, A. Lugli, I. Zlobec, J. van der Laak and I. Nagtegaal, "Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer",
Modern Pathology,
2023;36:100233.
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.
R. Leon-Ferre, J. Carter, D. Zahrieh, J. Sinnwell, R. Salgado, V. Suman, D. Hillman, J. Boughey, K. Kalari, F. Couch, J. Ingle, M. Balkenkohl, F. Ciompi, J. van der Laak and M. Goetz, "Abstract P2-11-34: Mitotic spindle hotspot counting using deep learning networks is highly associated with clinical outcomes in patients with early-stage triple-negative breast cancer who did not receive systemic therapy",
Cancer Research,
2023;83:P2-11-34-P2-11-34.
B. Guevara, N. Marini, S. Marchesin, W. Aswolinskiy, R. Schlimbach, D. Podareanu and F. Ciompi, "Caption generation from histopathology whole-slide images using pre-trained transformers",
Medical Imaging with Deep Learning,
2023.
R. Lomans, J. van der Laak, I. Nagtegaal, F. Ciompi and R. van der Post, "Deep learning for multi-class cell detection in H&E-stained slides of diffuse gastric cancer",
European Congress of Pathology,
2023.
R. Lomans, R. van der Post and F. Ciompi, "Interactive Cell Detection in H&E-stained slides of Diffuse Gastric Cancer",
Medical Imaging with Deep Learning,
2023.
M. D'Amato, M. Balkenhol, M. van Rijthoven, J. van der Laak and F. Ciompi, "On the robustness of regressing tumor percentage as an explainable detector in histopathology whole-slide images",
Medical Imaging with Deep Learning,
2023.
M. Aubreville, N. Stathonikos, C. Bertram, R. Klopfleisch, N. Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T. Donovan, A. Maier, M. Veta and K. Breininger, "Abstract: the MIDOG Challenge 2021",
Bildverarbeitung fur die Medizin, Workshop,
2023:115-115.