Sharing data for cancer research
Biblio
Data from: Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries. 2017. doi:10.17195/candat.2017.02.2.
Jochems-2017-MaastroDataUnbinned.csv (62.76 KB)

Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries. International Journal of Radiation Oncology*Biology*Physics. 2017;99(2):344 - 352. doi:10.1016/j.ijrobp.2017.04.021.
Data from: MMP2 small immuno protein antibody uptake in xenograft tumors is associated with MMP2 activity. 2015. doi:10.17195/candat.2015.10.6.
Panth_MMP2-activity-vs-uptake.csv (2.03 KB)
Panth_MMP2-analysis.csv (6.1 KB)
Panth_MMP2-representative-images.rar (570.44 KB)



Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006. doi:10.1038/ncomms5006.
Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial. Radiotherapy and Oncology. 2013;108(1):174 - 179. doi:10.1016/j.radonc.2012.09.019.
. Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer. Acta Oncol. 2013;52(7):1398-404. doi:10.3109/0284186X.2013.812795.
Preclinical evaluation and validation of [18F]HX4, a promising hypoxia marker for PET imaging. Proceedings of the National Academy of Sciences. 2011;108(35):14620 - 14625. doi:10.1073/pnas.1102526108.