Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Timo M. Deist"'
Autor:
Timo M. Deist, A. Jochems, Johan van Soest, Georgi Nalbantov, Cary Oberije, Seán Walsh, Michael Eble, Paul Bulens, Philippe Coucke, Wim Dries, Andre Dekker, Philippe Lambin
Publikováno v:
Clinical and Translational Radiation Oncology, Vol 4, Iss C, Pp 24-31 (2017)
Machine learning applications for personalized medicine are highly dependent on access to sufficient data. For personalized radiation oncology, datasets representing the variation in the entire cancer patient population need to be acquired and used t
Externí odkaz:
https://doaj.org/article/2905a7b17e9a42ca85049baed8e01b76
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031272493
Real-world problems are often multi-objective, with decision-makers unable to specify a priori which trade-off between the conflicting objectives is preferable. Intuitively, building machine learning solutions in such cases would entail providing mul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48789af5607f1389b9c117ddf1ba03bf
https://doi.org/10.1007/978-3-031-27250-9_8
https://doi.org/10.1007/978-3-031-27250-9_8
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031147203
Evolutionary algorithms (EAs) are well-known to be well suited for multi-objective (MO) optimization. However, especially in the case of real-valued variables, classic domination-based approaches are known to lose selection pressure when approaching
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::983b5cdf82395b5fe75065998539a11c
https://doi.org/10.1007/978-3-031-14721-0_13
https://doi.org/10.1007/978-3-031-14721-0_13
Autor:
Gareth J Price, Arthur Jochems, René Monshouwer, Jiayan Chen, Joost J. Nuyttens, M. Button, Johan van Soest, Carlotta Masciocchi, M. Scott Marshall, Andre Dekker, Priyanka Ojha, René M. Vernhout, Corinne Faivre-Finn, Frank J. W. M. Dankers, Philippe Lambin, Tomas Janssen, Timo M. Deist, Johan Bussink, Emiliano Spezi, Jiazhou Wang, Zhen Zhang, Vincenzo Valentini
Publikováno v:
Radiotherapy and Oncology, 144, 189-200
Radiotherapy and Oncology, 144, 189-200. Elsevier Ireland Ltd
Deist, T M, Dankers, F J W M, Ojha, P, Scott Marshall, M, Janssen, T, Faivre-finn, C, Masciocchi, C, Valentini, V, Wang, J, Chen, J, Zhang, Z, Spezi, E, Button, M, Jan Nuyttens, J, Vernhout, R, Van Soest, J, Jochems, A, Monshouwer, R, Bussink, J, Price, G, Lambin, P & Dekker, A 2020, ' Distributed learning on 20 000+ lung cancer patients – The Personal Health Train ', Radiotherapy and Oncology, vol. 144, pp. 189-200 . https://doi.org/10.1016/j.radonc.2019.11.019
Radiotherapy and Oncology, 144, pp. 189-200
Radiotherapy and Oncology, 144, 189-200. Elsevier Ireland Ltd
Deist, T M, Dankers, F J W M, Ojha, P, Scott Marshall, M, Janssen, T, Faivre-finn, C, Masciocchi, C, Valentini, V, Wang, J, Chen, J, Zhang, Z, Spezi, E, Button, M, Jan Nuyttens, J, Vernhout, R, Van Soest, J, Jochems, A, Monshouwer, R, Bussink, J, Price, G, Lambin, P & Dekker, A 2020, ' Distributed learning on 20 000+ lung cancer patients – The Personal Health Train ', Radiotherapy and Oncology, vol. 144, pp. 189-200 . https://doi.org/10.1016/j.radonc.2019.11.019
Radiotherapy and Oncology, 144, pp. 189-200
Background and purpose: Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) pro
Distributed radiomics as a signature validation study using the Personal Health Train infrastructure
Autor:
Johan Bussink, Andre Dekker, Frank J. W. M. Dankers, Hugo J.W.L. Aerts, Petros Kalendralis, Rianne Fijten, Alberto Traverso, Leonard Wee, Timo M. Deist, René Monshouwer, Ivan Zhovannik, Zhenwei Shi
Publikováno v:
Scientific Data, Vol 6, Iss 1, Pp 1-8 (2019)
Scientific Data, 6
Scientific Data
Scientific data, 6:218. Nature Publishing Group
Scientific Data, 6
Scientific Data
Scientific data, 6:218. Nature Publishing Group
Prediction modelling with radiomics is a rapidly developing research topic that requires access to vast amounts of imaging data. Methods that work on decentralized data are urgently needed, because of concerns about patient privacy. Previously publis
Autor:
Timo M. Deist, Cary Oberije, Andre Dekker, Issam El Naqa, Johan Bussink, Leonard Wee, Timothy D. Solberg, Wouter Bots, Olivier Morin, Frank J. W. M. Dankers, Margriet Kwint, Tim Lustberg, R. Wijsman, David R. Raleigh, I-Chow Hsu, Frank J. P. Hoebers, René Monshouwer, Johan van Soest, Philippe Lambin, José Belderbos, Gilmer Valdes, Arthur Jochems, Johannes H.A.M. Kaanders
Publikováno v:
Medical Physics. 46:1080-1087
Autor:
Christine E. Eyler, Andrew Patti, David Craft, Marleen Balvert, Timo M. Deist, Bas E. Dutilh, Alexander Schönhuth, Georgios Patoulidis
Publikováno v:
SSRN Electronic Journal.
Personalizing drug prescriptions in cancer care based on genomic information requires associating genomic markers with treatment effects. This is an unsolved challenge requiring genomic patient data in yet unavailable volumes as well as appropriate q
Autor:
Timo M. Deist, Akira Oyama, Boris Naujoks, Vanessa Volz, Koen van der Blom, Mariapia Marchi, Yusuke Nojima, Tea Tušar
Publikováno v:
Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
GECCO Companion
GECCO Companion
Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely unclear how they relate to real-world problems. What does an algorithm's performance on a benc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b1cdb3e79ea7ea7323294c625d0ba3f
https://hdl.handle.net/1887/3307602
https://hdl.handle.net/1887/3307602
Autor:
Chuck Mayo, Arthur Jochems, Andre Dekker, Jackson Reeves, Randall K. Ten Haken, Shruti Jolly, Timo M. Deist, Issam El Naqa, Johan van Soest, Marc L. Kessler, Philippe Lambin, Corinne Faivre-Finn, Dirk De Ruysscher, Gareth J Price, Cary Oberije, Martha M. Matuszak
Publikováno v:
International Journal of Radiation Oncology Biology Physics, 99(2), 344-352. Elsevier Science
Jochems, A, Deist, T M, El Naqa, I, Kessler, M, Mayo, C, Reeves, J, Jolly, S, Matuszak, M, Ten Haken, R, van Soest, J, Oberije, C, Faivre-Finn, C, Price, G, De Ruysscher, D, Lambin, P & Dekker, A 2017, ' Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries ', International Journal of Radiation: Oncology-Biology-Physics, vol. 99, no. 1, pp. 344-352 . https://doi.org/10.1016/j.ijrobp.2017.04.021
International Journal of Radiation Oncology, Biology, Physics
Faivre-Finn, C & et al 2017, ' Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries ' International Journal of Radiation: Oncology-Biology-Physics, vol 99, no. 1, pp. 344-352 . DOI: 10.1016/j.ijrobp.2017.04.021
Jochems, A, Deist, T M, El Naqa, I, Kessler, M, Mayo, C, Reeves, J, Jolly, S, Matuszak, M, Ten Haken, R, van Soest, J, Oberije, C, Faivre-Finn, C, Price, G, De Ruysscher, D, Lambin, P & Dekker, A 2017, ' Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries ', International Journal of Radiation: Oncology-Biology-Physics, vol. 99, no. 1, pp. 344-352 . https://doi.org/10.1016/j.ijrobp.2017.04.021
International Journal of Radiation Oncology, Biology, Physics
Faivre-Finn, C & et al 2017, ' Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries ' International Journal of Radiation: Oncology-Biology-Physics, vol 99, no. 1, pp. 344-352 . DOI: 10.1016/j.ijrobp.2017.04.021
Purpose Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on
Autor:
Andre Dekker, Wim Dries, Cary Oberije, Timo M. Deist, Sean Walsh, Arthur Jochems, Georgi Nalbantov, Philippe Coucke, Michael J. Eble, P. Bulens, Philippe Lambin, Johan van Soest
Publikováno v:
Clinical and Translational Radiation Oncology
Clinical and Translational Radiation Oncology, Vol 4, Iss C, Pp 24-31 (2017)
Clinical and Translational Radiation Oncology, 4, 24-31. Elsevier Ireland Ltd
Clinical and Translational Radiation Oncology, Vol 4, Iss C, Pp 24-31 (2017)
Clinical and Translational Radiation Oncology, 4, 24-31. Elsevier Ireland Ltd
Graphical abstract
Highlights • Developed and implemented IT infrastructure in 5 radiation clinics across 3 countries. • Proof-of-principle for ‘big data’ infrastructure and distributed learning studies. • General framework to execute
Highlights • Developed and implemented IT infrastructure in 5 radiation clinics across 3 countries. • Proof-of-principle for ‘big data’ infrastructure and distributed learning studies. • General framework to execute