Sharing data for cancer research
Biblio
Data from: 4DCT imaging to assess radiomics feature stability: an investigation for thoracic cancers. 2017. doi:10.17195/candat.2017.05.1.
Data from: 4DCT imaging to assess radiomics feature stability: an investigation for thoracic cancers. 2017. doi:10.17195/candat.2017.05.1.
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)

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.
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)





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.
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)





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.
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.