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2020 – today
- 2025
[j1]Joeran S. Bosma, Koen Dercksen, Luc Builtjes
, Romain André, Christian Roest, Stefan J. Fransen, Constant R. Noordman, Mar Navarro-Padilla, Judith Lefkes, Natália Alves, Max J. J. de Grauw, Leander van Eekelen, Joey Spronck, Megan Schuurmans, Bram de Wilde, Ward Hendrix, Witali Aswolinskiy, Anindo Saha, Jasper J. Twilt, Daan Geijs, Jeroen Veltman, Derya Yakar, Maarten de Rooij, Francesco Ciompi, Alessa Hering, Jeroen Geerdink, Henkjan Huisman, Quintin van Lohuizen, Michelle Stegeman, Karlijn Rutten, Inge M. E. Smit, Gijs Stultiens, Christiaan G. Overduin, M. J. C. M. Rutten, Ernst Th. Scholten, Rachel S. van der Post, Katrien Grunberg, Shoko Vos, Elise M. G. Taken, Iris D. Nagtegaal, Anne Mickan, Miriam Groeneveld, Paul K. Gerke, James A. Meakin, Monika Looijen-Salamon, Tijmen L. M. de Haas, Fabian Hoitsma, Marina D'Amato:
The DRAGON benchmark for clinical NLP. npj Digit. Medicine 8(1) (2025)- 2023
- [c3]Joeran Bosma, Dre Peeters, Natália Alves, Anindo Saha, Zaigham Saghir, Colin Jacobs, Henkjan Huisman:
Reproducibility of Training Deep Learning Models for Medical Image Analysis. MIDL 2023: 1269-1287 - [d1]Max De Grauw, Natália Alves, Megan Schuurmans, Henkjan Huisman, Bram van Ginneken, Alessa Hering:
The ULS23 Challenge Public Training Dataset. Zenodo, 2023
- [i2]Jun Ma, Yao Zhang, Song Gu, Cheng Ge, Shihao Ma, Adamo Young, Cheng Zhu, Kangkang Meng, Xin Yang, Ziyan Huang, Fan Zhang, Wentao Liu, YuanKe Pan, Shoujin Huang, Jiacheng Wang, Mingze Sun, Weixin Xu, Dengqiang Jia, Jae Won Choi, Natália Alves, Bram de Wilde, Gregor Köhler, Yajun Wu, Manuel Wiesenfarth, Qiongjie Zhu, Guoqiang Dong, Jian He, FLARE Challenge Consortium, Bo Wang:
Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge. CoRR abs/2308.05862 (2023) - 2022
- [c2]Natália Alves, Bram de Wilde:
Uncertainty-Guided Self-learning Framework for Semi-supervised Multi-organ Segmentation. FLARE@MICCAI 2022: 116-127 - 2021
- [c1]Natália Alves, Joana Dias, Tiago Ventura, Josefina Mateus, Miguel Capela, Leila Khouri, Maria do Carmo Lopes:
Predicting the Need for Adaptive Radiotherapy in Head and Neck Patients from CT-Based Radiomics and Pre-treatment Data. ICCSA (5) 2021: 429-444 - [i1]Natália Alves, Megan Schuurmans, Geke Litjens, Joeran S. Bosma, John Hermans, Henkjan Huisman:
Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography. CoRR abs/2111.15409 (2021)
Coauthor Index
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