| Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge AAA Setio, A Traverso, T De Bel, MSN Berens, C Van Den Bogaard, ... Medical image analysis 42, 1-13, 2017 | 1064 | 2017 |
| Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study W Bulten, H Pinckaers, H van Boven, R Vink, T de Bel, B van Ginneken, ... The Lancet Oncology 21 (2), 233-241, 2020 | 556 | 2020 |
| Deep learning–based histopathologic assessment of kidney tissue M Hermsen, T de Bel, M Den Boer, EJ Steenbergen, J Kers, S Florquin, ... Journal of the American Society of Nephrology 30 (10), 1968-1979, 2019 | 268 | 2019 |
| Stain-transforming cycle-consistent generative adversarial networks for improved segmentation of renal histopathology T de Bel, M Hermsen, J Kers, J van der Laak, G Litjens | 94 | 2018 |
| 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 | 79 | 2021 |
| Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer Z Swiderska-Chadaj, T de Bel, L Blanchet, A Baidoshvili, D Vossen, ... Scientific Reports 10 (1), 14398, 2020 | 63 | 2020 |
| Automatic segmentation of histopathological slides of renal tissue using deep learning T de Bel, M Hermsen, B Smeets, L Hilbrands, J van der Laak, G Litjens Medical Imaging 2018: Digital Pathology 10581, 285-290, 2018 | 56 | 2018 |
| Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics MCA Balkenhol, F Ciompi, Ż Świderska-Chadaj, R van de Loo, M Intezar, ... The Breast 56, 78-87, 2021 | 22 | 2021 |
| Automated prediction of low ferritin concentrations using a machine learning algorithm S Kurstjens, T De Bel, A van der Horst, R Kusters, J Krabbe, ... Clinical Chemistry and Laboratory Medicine (CCLM) 60 (12), 1921-1928, 2022 | 15 | 2022 |
| Renal phospholipidosis and impaired magnesium handling in high‐fat‐diet–fed mice S Kurstjens, B Smeets, C Overmars-Bos, HB Dijkman, DJW den Braanker, ... The FASEB Journal 33 (6), 7192-7201, 2019 | 14 | 2019 |
| Structure instance segmentation in renal tissue: A case study on tubular immune cell detection T de Bel, M Hermsen, G Litjens, J van der Laak Computational Pathology and Ophthalmic Medical Image Analysis: First …, 2018 | 8 | 2018 |
| Artificial Intelligence in Pediatric Pathology: The Extinction of a Medical Profession or the Key to a Bright Future? A van der Kamp, TJ Waterlander, T de Bel, J van der Laak, ... Pediatric and Developmental Pathology 25 (4), 380-387, 2022 | 6 | 2022 |
| Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning T de Bel, G Litjens, J Ogony, M Stallings-Mann, JM Carter, T Hilton, ... NPJ breast cancer 8 (1), 13, 2022 | 6 | 2022 |
| High resolution microCT to analyze the 3D morphology of microcalcifications in benign breast disease and breast cancer biopsy tissues SE Schrup, T de Bel, T Hoskin, T Allers, S Winham, D Radisky, ... Cancer Research 83 (7_Supplement), 3587-3587, 2023 | 1 | 2023 |
| Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence J Ogony, T de Bel, DC Radisky, J Kachergus, EA Thompson, AC Degnim, ... Breast Cancer Research 24 (1), 45, 2022 | 1 | 2022 |
| Reply to:“Addressing Chatbots as Artificial Intelligence Aids in Pediatric Pathology” A van der Kamp, TJ Waterlander, T de Bel, J van der Laak, ... Pediatric and Developmental Pathology, 10935266241237904, 2024 | | 2024 |
| Automated Deep Learning-Based Classification of Wilms Tumor Histopathology A van der Kamp, T de Bel, L van Alst, J Rutgers, ... Cancers 15 (9), 2656, 2023 | | 2023 |
| Serum hormone levels and normal breast histology among premenopausal women ME Sherman, T de Bel, MG Heckman, LJ White, J Ogony, ... Breast cancer research and treatment 194 (1), 149-158, 2022 | | 2022 |
| Abstract P2-11-14: Pathology AI features and immune biomarkers of postpartum involution: Implications for postpartum breast cancer JW Ogony, T De Bel, D Radisky, J VanderLaak, M Sherman Cancer Research 82 (4_Supplement), P2-11-14-P2-11-14, 2022 | | 2022 |
| Optimised tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics M Balkenhol, F Ciompi, Z Swiderska-Chadaj, R van de Loo, M Intezar, ... VIRCHOWS ARCHIV 477, S36-S37, 2020 | | 2020 |
