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Table 1 Overview of the datasets

From: The effect of feature normalization methods in radiomics

Dataset

N

d

Modality

Tumor type

DOI

Arita2018

168

685

MRI

Brain

10.1038/s41598-018–30273-4

Carvalho2018

262

118

FDG - PET

NSCLC

10.1371/journal.pone.0192859

Hosny2018A

293

1005

CT

NSCLC

10.1371/journal.pmed.1002711

Hosny2018B

211

1005

CT

NSCLC

10.1371/journal.pmed.1002711

Hosny2018C

183

1005

CT

NSCLC

10.1371/journal.pmed.1002711

Ramella2018

91

243

CT

NSCLC

10.1371/journal.pone.0207455

Saha2018

922

530

DCE-MRI

Breast

10.1038/s41416-018–0185-8

Lu2019

213

658

CT

Ovarian cancer

10.1038/s41467-019–08718-9

Sasaki2019

138

588

MRI

Brain

10.1038/s41598-019–50849-y

Toivonen2019

100

7106

MRI

Prostate cancer

10.1371/journal.pone.0217702

Keek2020

273

1323

CT

HNSCC

10.1371/journal.pone.0232639

Li2020

51

397

MRI

Glioma

10.1371/journal.pone.0227703

Park2020

768

941

US

Thyroid cancer

10.1371/journal.pone.0227315

Song2020

260

265

MRI

Prostate cancer

10.1371/journal.pone.0237587

Veeraraghavan2020

150

201

DCE-MRI

Breast

10.1038/s41598-020–72475-9

  1. N sample size, d number of features, DOI digital object identifier of the publication corresponding to the dataset