| Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology D Tellez, G Litjens, P Bándi, W Bulten, JM Bokhorst, F Ciompi, ... Medical image analysis 58, 101544, 2019 | 280 | 2019 |
| Residual cyclegan for robust domain transformation of histopathological tissue slides T de Bel, JM Bokhorst, J van der Laak, G Litjens Medical Image Analysis 70, 102004, 2021 | 37 | 2021 |
| Learning from sparsely annotated data for semantic segmentation in histopathology images JM Bokhorst, H Pinckaers, P van Zwam, I Nagtegaal, J van der Laak, ... | 37 | 2019 |
| Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning JM Bokhorst, A Blank, A Lugli, I Zlobec, H Dawson, M Vieth, ... Modern pathology 33 (5), 825-833, 2020 | 24 | 2020 |
| Improving tumor budding reporting in colorectal cancer: a Delphi consensus study TS Haddad, A Lugli, S Aherne, V Barresi, B Terris, JM Bokhorst, ... Virchows Archiv, 1-11, 2021 | 15 | 2021 |
| Taking tumour budding to the next frontier—a post International Tumour Budding Consensus Conference (ITBCC) 2016 review L Studer, A Blank, JM Bokhorst, ID Nagtegaal, I Zlobec, A Lugli, A Fischer, ... Histopathology 78 (4), 476-484, 2021 | 14 | 2021 |
| Are tumour grade and tumour budding equivalent in colorectal cancer? A retrospective analysis of 771 patients I Zlobec, HE Dawson, A Blank, JM Bokhorst, MD Berger, ID Nagtegaal, ... European journal of cancer 130, 139-145, 2020 | 13 | 2020 |
| Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations N Marini, S Marchesin, S Otálora, M Wodzinski, A Caputo, ... NPJ digital medicine 5 (1), 102, 2022 | 9 | 2022 |
| Automatic detection of tumor budding in colorectal carcinoma with deep learning JM Bokhorst, L Rijstenberg, D Goudkade, I Nagtegaal, J van der Laak, ... Computational Pathology and Ophthalmic Medical Image Analysis: First …, 2018 | 8 | 2018 |
| Mathematical models for tumor growth and the reduction of overtreatment BL Heesterman, JM Bokhorst, LMH de Pont, BM Verbist, JP Bayley, ... Journal of Neurological Surgery Part B: Skull Base 80 (01), 072-078, 2019 | 6 | 2019 |
| Shrinkage versus fragmentation response in neoadjuvantly treated oesophageal adenocarcinoma: significant prognostic relevance C Graham Martinez, S Kus Öztürk, A Al‐Kaabi, MJ Valkema, JM Bokhorst, ... Histopathology 80 (6), 982-994, 2022 | 3 | 2022 |
| Correction to: Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning JM Bokhorst, A Blank, A Lugli, I Zlobec, H Dawson, M Vieth, ... Modern Pathology 33 (5), 981-981, 2020 | 1 | 2020 |
| Deep learning based tumor–stroma ratio scoring in colon cancer correlates with microscopic assessment MA Smit, F Ciompi, JM Bokhorst, GW van Pelt, OGF Geessink, H Putter, ... Journal of Pathology Informatics, 100191, 2023 | | 2023 |
| Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer C Mercan, M Balkenhol, R Salgado, M Sherman, P Vielh, W Vreuls, ... NPJ breast cancer 8 (1), 120, 2022 | | 2022 |
| Semi-supervised learning to automate tumor bud detection in cytokeratin-stained whole-slide images of colorectal cancer JM Bokhorst, ID Nagtegaal, I Zlobec, H Dawson, K Sheahan, F Simmer, ... | | 2022 |
| Building-T-cell score is a potential predictor for more aggressive treatment in pT1 colorectal cancers L Studer, JM Bokhorst, F Ciompi, A Fischer, H Dawson Proceedings of the ECDP 2022 18th European Congress on Digital Pathology, 15 …, 2022 | | 2022 |
| Redefining patterns of tumour response to chemoradiotherapy in oesophageal cancer with the aid of ai CG Martinez, A Al-Kaabi, T Strausz, J Bokhorst, C Rosman, P Siersema, ... VIRCHOWS ARCHIV 477, S185-S185, 2020 | | 2020 |
| Computer-assisted hot-spot selection for tumour budding assessment in colorectal cancer J Bokhorst, F Ciompi, I Zlobec, A Lugli, M Vieth, R Kirsch, J van der Laak, ... VIRCHOWS ARCHIV 477, S14-S14, 2020 | | 2020 |
| Characterisation of the tumour-host interface as a prognostic factor through deep learning systems T Haddad, J Bokhorst, L van den Dobbelsteen, F Zimmer, F Ciompi, ... VIRCHOWS ARCHIV 477, S38-S38, 2020 | | 2020 |
| Validation of computer-assisted tumour-bud and T-cell detection in pT1 colorectal cancer L Studer, J Bokhorst, I Zlobec, A Lugli, A Fischer, F Ciompi, J van der Laak, ... VIRCHOWS ARCHIV 477, S37-S38, 2020 | | 2020 |
