Search Results - "Deist, Timo M"

TESS3: fast inference of spatial population structure and genome scans for selection by Caye, Kevin, Deist, Timo M., Martins, Helena, Michel, Olivier, François, Olivier

“…Geography and landscape are important determinants of genetic variation in natural populations, and several ancestry estimation methods have been proposed to…”
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Radiomics: the bridge between medical imaging and personalized medicine by Lambin, Philippe, Leijenaar, Ralph T.H., Deist, Timo M., Peerlings, Jurgen, de Jong, Evelyn E.C., van Timmeren, Janita, Sanduleanu, Sebastian, Larue, Ruben T.H.M., Even, Aniek J.G., Jochems, Arthur, van Wijk, Yvonka, Woodruff, Henry, van Soest, Johan, Lustberg, Tim, Roelofs, Erik, van Elmpt, Wouter, Dekker, Andre, Mottaghy, Felix M., Wildberger, Joachim E., Walsh, Sean

“…Key Points Radiomics is becoming increasingly more important in medical imaging The explosion of medical imaging data creates an environment ideal for…”
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Distributed learning: Developing a predictive model based on data from multiple hospitals without data leaving the hospital – A real life proof of concept by Jochems, Arthur, Deist, Timo M, van Soest, Johan, Eble, Michael, Bulens, Paul, Coucke, Philippe, Dries, Wim, Lambin, Philippe, Dekker, Andre

“…Abstract Purpose One of the major hurdles in enabling personalized medicine is obtaining sufficient patient data to feed into predictive models. Combining data…”
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Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers by Deist, Timo M., Dankers, Frank J. W. M., Valdes, Gilmer, Wijsman, Robin, Hsu, I‐Chow, Oberije, Cary, Lustberg, Tim, Soest, Johan, Hoebers, Frank, Jochems, Arthur, El Naqa, Issam, Wee, Leonard, Morin, Olivier, Raleigh, David R., Bots, Wouter, Kaanders, Johannes H., Belderbos, José, Kwint, Margriet, Solberg, Timothy, Monshouwer, René, Bussink, Johan, Dekker, Andre, Lambin, Philippe

“…Purpose Machine learning classification algorithms (classifiers) for prediction of treatment response are becoming more popular in radiotherapy literature…”
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Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: euroCAT by Deist, Timo M., Jochems, A., van Soest, Johan, Nalbantov, Georgi, Oberije, Cary, Walsh, Seán, Eble, Michael, Bulens, Paul, Coucke, Philippe, Dries, Wim, Dekker, Andre, Lambin, Philippe

“…[Display omitted] •Developed and implemented IT infrastructure in 5 radiation clinics across 3 countries.•Proof-of-principle for ‘big data’ infrastructure and…”
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Simulation-assisted machine learning by Deist, Timo M, Patti, Andrew, Wang, Zhaoqi, Krane, David, Sorenson, Taylor, Craft, David

“…Abstract Motivation In a predictive modeling setting, if sufficient details of the system behavior are known, one can build and use a simulation for making…”
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Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries by Jochems, Arthur, Deist, Timo M., El Naqa, Issam, Kessler, Marc, Mayo, Chuck, Reeves, Jackson, Jolly, Shruti, Matuszak, Martha, Ten Haken, Randall, van Soest, Johan, Oberije, Cary, Faivre-Finn, Corinne, Price, Gareth, de Ruysscher, Dirk, Lambin, Philippe, Dekker, Andre

“…Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this…”
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Distributed learning on 20 000+ lung cancer patients – The Personal Health Train by Deist, Timo M., Dankers, Frank J.W.M., Ojha, Priyanka, Scott Marshall, M., Janssen, Tomas, Faivre-Finn, Corinne, Masciocchi, Carlotta, Valentini, Vincenzo, Wang, Jiazhou, Chen, Jiayan, Zhang, Zhen, Spezi, Emiliano, Button, Mick, Jan Nuyttens, Joost, Vernhout, René, van Soest, Johan, Jochems, Arthur, Monshouwer, René, Bussink, Johan, Price, Gareth, Lambin, Philippe, Dekker, Andre

“…•Machine learning without sharing patient data, quickly and at scale.•Connecting 8 oncology institutes from 5 countries.•Survival prediction modelling on…”
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Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer by Bogowicz, Marta, Jochems, Arthur, Deist, Timo M., Tanadini-Lang, Stephanie, Huang, Shao Hui, Chan, Biu, Waldron, John N., Bratman, Scott, O’Sullivan, Brian, Riesterer, Oliver, Studer, Gabriela, Unkelbach, Jan, Barakat, Samir, Brakenhoff, Ruud H., Nauta, Irene, Gazzani, Silvia E., Calareso, Giuseppina, Scheckenbach, Kathrin, Hoebers, Frank, Wesseling, Frederik W. R., Keek, Simon, Sanduleanu, Sebastian, Leijenaar, Ralph T. H., Vergeer, Marije R., Leemans, C. René, Terhaard, Chris H. J., van den Brekel, Michiel W. M., Hamming-Vrieze, Olga, van der Heijden, Martijn A., Elhalawani, Hesham M., Fuller, Clifton D., Guckenberger, Matthias, Lambin, Philippe

“…A major challenge in radiomics is assembling data from multiple centers. Sharing data between hospitals is restricted by legal and ethical regulations…”
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Decision support systems for personalized and participative radiation oncology by Lambin, Philippe, Zindler, Jaap, Vanneste, Ben G.L., De Voorde, Lien Van, Eekers, Daniëlle, Compter, Inge, Panth, Kranthi Marella, Peerlings, Jurgen, Larue, Ruben T.H.M., Deist, Timo M., Jochems, Arthur, Lustberg, Tim, van Soest, Johan, de Jong, Evelyn E.C., Even, Aniek J.G., Reymen, Bart, Rekers, Nicolle, van Gisbergen, Marike, Roelofs, Erik, Carvalho, Sara, Leijenaar, Ralph T.H., Zegers, Catharina M.L., Jacobs, Maria, van Timmeren, Janita, Brouwers, Patricia, Lal, Jonathan A., Dubois, Ludwig, Yaromina, Ala, Van Limbergen, Evert Jan, Berbee, Maaike, van Elmpt, Wouter, Oberije, Cary, Ramaekers, Bram, Dekker, Andre, Boersma, Liesbeth J., Hoebers, Frank, Smits, Kim M., Berlanga, Adriana J., Walsh, Sean

“…A paradigm shift from current population based medicine to personalized and participative medicine is underway. This transition is being supported by the…”
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Distributed radiomics as a signature validation study using the Personal Health Train infrastructure by Shi, Zhenwei, Zhovannik, Ivan, Traverso, Alberto, Dankers, Frank J. W. M., Deist, Timo M., Kalendralis, Petros, Monshouwer, René, Bussink, Johan, Fijten, Rianne, Aerts, Hugo J. W. L., Dekker, Andre, Wee, Leonard

“…Prediction modelling with radiomics is a rapidly developing research topic that requires access to vast amounts of imaging data. Methods that work on…”
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Modern clinical research: How rapid learning health care and cohort multiple randomised clinical trials complement traditional evidence based medicine by Lambin, Philippe, Zindler, Jaap, Vanneste, Ben, van de Voorde, Lien, Jacobs, Maria, Eekers, Daniëlle, Peerlings, Jurgen, Reymen, Bart, Larue, Ruben T H M, Deist, Timo M, de Jong, Evelyn E C, Even, Aniek J G, Berlanga, Adriana J, Roelofs, Erik, Cheng, Qing, Carvalho, Sara, Leijenaar, Ralph T H, Zegers, Catharina M L, van Limbergen, Evert, Berbee, Maaike, van Elmpt, Wouter, Oberije, Cary, Houben, Ruud, Dekker, Andre, Boersma, Liesbeth, Verhaegen, Frank, Bosmans, Geert, Hoebers, Frank, Smits, Kim, Walsh, Sean

“…Trials are vital in informing routine clinical care; however, current designs have major deficiencies. An overview of the various challenges that face modern…”
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Erratum: “Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers” [Med. Phys. 45 (7), 3449‐3459 (2018)] by Deist, Timo M., Dankers, Frank J. W. M., Valdes, Gilmer, Wijsman, Robin, Hsu, I‐Chow, Oberije, Cary, Lustberg, Tim, Soest, Johan, Hoebers, Frank, Jochems, Arthur, El Naqa, Issam, Wee, Leonard, Morin, Olivier, Raleigh, David R., Bots, Wouter, Kaanders, Johannes H., Belderbos, José, Kwint, Margriet, Solberg, Timothy, Monshouwer, René, Bussink, Johan, Dekker, Andre, Lambin, Philippe

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Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries by Jochems, Arthur, PhD, Deist, Timo M., Msc, El Naqa, Issam, PhD, Kessler, Marc, PhD, Mayo, Chuck, PhD, Reeves, Jackson, MD, Jolly, Shruti, MD PhD, Matuszak, Martha, MD, Haken, Randall Ten, PhD, van Soest, Johan, Msc, Oberije, Cary, PhD, Faivre-Finn, Corinne, MD PhD, Price, Gareth, PhD, de Ruysscher, Dirk, MD PhD, Lambin, Philippe, MD PhD, Dekker, Andre, PhD

“…Abstract Purpose Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with (chemo)radiotherapy are of limited quality. In this…”
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Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent by Deist, Timo M, Maree, Stefanus C, Alderliesten, Tanja, Bosman, Peter A. N

“…B\"ack T. et al. (eds) Parallel Problem Solving from Nature - PPSN XVI. PPSN 2020. Lecture Notes in Computer Science, vol 12270. Springer, Cham Evolutionary…”
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Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization by Deist, Timo M, Grewal, Monika, Dankers, Frank J. W. M, Alderliesten, Tanja, Bosman, Peter A. N

“…Real-world problems are often multi-objective with decision-makers unable to specify a priori which trade-off between the conflicting objectives is preferable…”
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High-dose-rate prostate brachytherapy inverse planning on dose-volume criteria by simulated annealing by Deist, Timo M, Gorissen, Bram L

“…Physics in Medicine and Biology, 61(3), 1155-1170, 2016 High-dose-rate brachytherapy is a tumor treatment method where a highly radioactive source is brought…”
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Identifying Properties of Real-World Optimisation Problems through a Questionnaire by van der Blom, Koen, Deist, Timo M, Volz, Vanessa, Marchi, Mariapia, Nojima, Yusuke, Naujoks, Boris, Oyama, Akira, Tušar, Tea

“…Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences. However, it is not clear how closely benchmarks match…”
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Simulation assisted machine learning by Deist, Timo M, Patti, Andrew, Wang, Zhaoqi, Krane, David, Sorenson, Taylor, Craft, David

“…Motivation: In a predictive modeling setting, if sufficient details of the system behavior are known, one can build and use a simulation for making…”
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Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems by van der Blom, Koen, Deist, Timo M, Tušar, Tea, Marchi, Mariapia, Nojima, Yusuke, Oyama, Akira, Volz, Vanessa, Naujoks, Boris

“…Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely…”
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