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Table 2 Demographics of patients among different dataset

From: Fully automated pelvic bone segmentation in multiparameteric MRI using a 3D convolutional neural network

Characteristic Algorithm development# (N = 264) External Set* (N = 60) F Value P value
Training set Validation set Testing set
No. of patients 208 28 28 60
Age (mean, years) (SD) 67.13 (9.75) 67.03 (9.93) 67.21 (9.35) 65.38 (13.07) 0.458 0.712
PSA (median, ng/ml)
 T-PSA (range) 10.34 (0.15, 156.00) 9.01 (0.77, 128.3) 8.96 (0.82, 27.99) 8.14 (1.38, 50.00) 1.349 0.259
 F-PSA (range) 1.32 (0.09, 23.46) 1.08 (0.46, 9.05) 1.32 (0.34, 3.53) 1.43 (0.33, 13.20) 0.342 0.795
 F/T-PSA (range) 0.13 (0.02, 0.36) 0.13 (0.05, 0.26) 0.16 (0.05, 0.24) 0.14 (0.05, 0.65) 2.077 0.104
  1. SD standard deviation, PSA prostate specific antigen, T-PSA total PSA, F-PSA free PSA
  2. #The data in algorithm development were collected between August 2018 and August 2019
  3. *The data in external validation were collected between January 2020 and March 2020