| Radiomics: the bridge between medical imaging and personalized medicine P Lambin, RTH Leijenaar, TM Deist, J Peerlings, EEC de Jong, ... Nature Reviews Clinical Oncology 14 (12), 749, 2017 | 4025 | 2017 |
| Machine learning algorithms for outcome prediction in (chemo) radiotherapy: An empirical comparison of classifiers TM Deist, FJWM Dankers, G Valdes, R Wijsman, IC Hsu, C Oberije, ... Medical physics 45 (7), 3449-3459, 2018 | 280 | 2018 |
| TESS3: fast inference of spatial population structure and genome scans for selection K Caye, TM Deist, H Martins, O Michel, O François Molecular ecology resources 16 (2), 540-548, 2016 | 271 | 2016 |
| Distributed learning: Developing a predictive model based on data from multiple hospitals without data leaving the hospital–A real life proof of concept A Jochems, TM Deist, J van Soest, M Eble, P Bulens, P Coucke, W Dries, ... Radiotherapy and Oncology 121 (3), 459-467, 2016 | 210 | 2016 |
| Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: euroCAT TM Deist, A Jochems, J van Soest, G Nalbantov, C Oberije, S Walsh, ... Clinical and Translational Radiation Oncology 4, 24-31, 2017 | 168 | 2017 |
| Decision support systems for personalized and participative radiation oncology P Lambin, J Zindler, BGL Vanneste, L Van De Voorde, D Eekers, ... Advanced drug delivery reviews 109, 131-153, 2017 | 154 | 2017 |
| Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries A Jochems, TM Deist, I El Naqa, M Kessler, C Mayo, J Reeves, S Jolly, ... International Journal of Radiation Oncology* Biology* Physics 99 (2), 344-352, 2017 | 148 | 2017 |
| Distributed learning on 20 000+ lung cancer patients–The Personal Health Train TM Deist, FJWM Dankers, P Ojha, MS Marshall, T Janssen, C Faivre-Finn, ... Radiotherapy and Oncology 144, 189-200, 2020 | 138 | 2020 |
| Simulation-assisted machine learning TM Deist, A Patti, Z Wang, D Krane, T Sorenson, D Craft Bioinformatics 35 (20), 4072-4080, 2019 | 76 | 2019 |
| Modern clinical research: How rapid learning health care and cohort multiple randomised clinical trials complement traditional evidence based medicine P Lambin, J Zindler, B Vanneste, L Van De Voorde, M Jacobs, D Eekers, ... Acta Oncologica 54 (9), 1289-1300, 2015 | 74 | 2015 |
| Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer M Bogowicz, A Jochems, TM Deist, S Tanadini-Lang, SH Huang, B Chan, ... Scientific Reports 10 (1), 1-10, 2020 | 63 | 2020 |
| Distributed radiomics as a signature validation study using the Personal Health Train infrastructure Z Shi, I Zhovannik, A Traverso, FJWM Dankers, TM Deist, P Kalendralis, ... Scientific data 6 (1), 1-8, 2019 | 59 | 2019 |
| Big Data in radiation therapy: challenges and opportunities T Lustberg, J van Soest, A Jochems, T Deist, Y van Wijk, S Walsh, ... The British journal of radiology 90 (1069), 20160689, 2017 | 45 | 2017 |
| High-dose-rate prostate brachytherapy inverse planning on dose-volume criteria by simulated annealing TM Deist, BL Gorissen Physics in Medicine & Biology 61 (3), 1155, 2016 | 40 | 2016 |
| Distributed learning to protect privacy in multi-centric clinical studies A Damiani, M Vallati, R Gatta, N Dinapoli, A Jochems, T Deist, ... Conference on Artificial Intelligence in Medicine in Europe, 65-75, 2015 | 36 | 2015 |
| Validation of effective dose as a better predictor of radiation pneumonitis risk than mean lung dose: Secondary analysis of a randomized trial SL Tucker, T Xu, H Paganetti, T Deist, V Verma, N Choi, R Mohan, Z Liao International Journal of Radiation Oncology* Biology* Physics 103 (2), 403-410, 2019 | 30 | 2019 |
| Can radiomics help to predict skeletal muscle response to chemotherapy in stage IV non-small cell lung cancer? EEC de Jong, KJC Sanders, TM Deist, W van Elmpt, A Jochems, ... European Journal of Cancer 120, 107-113, 2019 | 26 | 2019 |
| Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization TM Deist, M Grewal, FJWM Dankers, T Alderliesten, PAN Bosman arXiv preprint arXiv:2102.04523, 2021 | 14 | 2021 |
| An end-to-end deep learning approach for landmark detection and matching in medical images M Grewal, TM Deist, J Wiersma, PAN Bosman, T Alderliesten Medical Imaging 2020: Image Processing 11313, 1131328, 2020 | 12 | 2020 |
| Identifying Properties of Real-World Optimisation Problems through a Questionnaire K van der Blom, TM Deist, V Volz, M Marchi, Y Nojima, B Naujoks, ... arXiv preprint arXiv:2011.05547, 2020 | 11 | 2020 |
