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Timo Deist
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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
43032017
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
2872018
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
2822016
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
2132016
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
1712017
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
1582017
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
1492017
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
1442020
Simulation-assisted machine learning
TM Deist, A Patti, Z Wang, D Krane, T Sorenson, D Craft
Bioinformatics 35 (20), 4072-4080, 2019
802019
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
742015
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
652020
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
622019
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
462017
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
402016
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
362015
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
312019
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
262019
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
172021
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
132020
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
122020
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