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CanDat - 2018 Eekers - Data LGG .ods (157.14 KB) CanDat - 2018 Eekers - Data LGG .xlsx (183.07 KB)

Eekers DBP. Optimization of Brain and Head & Neck Radiotherapy. GROW - School for Oncology and Developmental Biology. 2018;Ph.D.:201. doi:10.17195/candat.2018.12.7.

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2018-Eekers-Thesis.pdf (5.47 MB) 2018-Eekers-Propositions.pdf (381.59 KB) 2018-Eekers-Thesis-Summary.pdf (318.74 KB)

Eekers DBP, Ven Lin 't, Deprez S, et al. The posterior cerebellum, a new organ at risk?. Clinical and Translational Radiation Oncology. 2018;8:22 - 26. doi:10.1016/j.ctro.2017.11.010.

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van Timmeren J, Leijenaar RTH, van Elmpt W, et al. Data from: Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images. 2017. doi:10.17195/candat.2017.02.1.

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Van-Timmeren_2017_cases-001-020.zip (750.99 MB) Van-Timmeren_2017_cases-021-040.zip (726.98 MB) Van-Timmeren_2017_cases-041-060.zip (777.6 MB) Van-Timmeren_2017_cases-061-080.zip (795.72 MB) Van-Timmeren_2017_cases-081-102.zip (827.01 MB)

Eekers D, Roelofs E, Jelen U, et al. Data from: Benefit of particle therapy in re-irradiation of head and neck patients. Results of a multicenter in silico ROCOCO trial. 2016. doi:10.17195/candat.2016.04.2.

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Carvalho S, Troost EGC, Bons J, Menheere P, Lambin P, Oberije C. Data from: Prognostic value of blood-biomarkers related to hypoxia, inflammation, immune response and tumour load in non-small cell lung cancer – a survival model with external validation. 2016. doi:10.17195/candat.2016.04.1.

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carvalho-prognostic-biomarkers-NSCLC.xlsx (69.51 KB)

Even A, Hamming-Vrieze O, van Elmpt W, et al. Data from: Quantitative assessment of Zirconium-89 labeled cetuximab using PETCT imaging in patients with advanced head and neck cancer - a theragnostic approach. 2016. doi:10.17195/candat.2016.11.1.

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Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB)

Roelofs E. From Data to Decision - A Knowledge Engineering approach to individualise cancer therapy. GROW - School for Oncology and Developmental Biology. 2016;Ph.D.:175. doi:10.17195/candat.2016.07.01.

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Lambin P. Radiomics Digital Phantom. 2016. doi:10.17195/candat.2016.08.1.

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PHANTOM_DICOM.zip (7.73 MB) GTV_B_DICOM.zip (281.74 KB) GTV_M_DICOM.zip (175.39 KB) GTV_O_DICOM.zip (421.42 KB)

Walsh S, Roelofs E, Kuess P, et al. Data from: A validated Tumor Control Probability model based on a meta-analysis of low, intermediate, and high-risk prostate cancer patients treated by photon, proton, or carbon-ion radiotherapy. 2015. doi:10.17195/candat.2015.10.8.

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Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (CSV) (15.82 KB) Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (XLS) (13.85 KB)

Cheng Q, Roelofs E, Ramaekers B, et al. Data from: Development and Evaluation of an Online Three-Level Proton vs Photon Decision Support Prototype for Head and Neck Cancer - Comparison of Dose, Toxicity and Cost-Effectiveness. 2015. doi:10.17195/candat.2015.10.5.

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Panth K, van den Beucken T, Biemans R, et al. Data from: MMP2 small immuno protein antibody uptake in xenograft tumors is associated with MMP2 activity. 2015. doi:10.17195/candat.2015.10.6.

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Panth_MMP2-activity-vs-uptake.csv (2.03 KB) Panth_MMP2-analysis.csv (6.1 KB) Panth_MMP2-representative-images.rar (570.44 KB)

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