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. 2021 Nov 24;12:172. doi: 10.1186/s13244-021-01115-1

Table 1.

Overview of the datasets

Dataset N d Dimensionality (#Samples/#Features) Outcome balance (%) Modality Tumor type DOI
Carvalho2018 [30] 262 117 2.22 59 FDG-PET NSCLC 10.1371/journal.pone.0192859
Hosny2018A (HarvardRT) [31] 293 1004 0.29 54 CT NSCLC 10.1371/journal.pmed.1002711
Hosny2018B (Maastro) [31] 211 1004 0.21 28 CT NSCLC 10.1371/journal.pmed.1002711
Hosny2018C (Moffitt) [31] 183 1004 0.18 73 CT NSCLC 10.1371/journal.pmed.1002711
Ramella2018 [32] 91 242 0.37 55 CT NSCLC 10.1371/journal.pone.0207455
Toivonen2019 [33] 100 7105 0.01 60 MRI Prostate Cancer 10.1371/journal.pone.0217702
Keek2020 [34] 273 1322 0.21 40 CT HNSCC 10.1371/journal.pone.0232639
Li2020 [35] 51 396 0.13 63 MRI Glioma 10.1371/journal.pone.0227703
Park2020 [36] 768 940 0.82 24 US Thyroid Cancer 10.1371/journal.pone.0227315
Song2020 [37] 260 264 0.98 49 MR Prostate Cancer 10.1371/journal.pone.0237587

Overview of all radiomics datasets used. Only publicly available datasets were included to allow for easy reproducibility. N denotes the sample size, while d denotes the number of features (corresponding to the dimension of the data). The outcome balance measures the number of events in the outcome. DOI denotes the identifier of the publication corresponding to the dataset