Skip to main content

Table 3 Diagnostic performances of the radiomics model for differentiating pseudoprogression from true progression versus the radiologists’ assessment

From: Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T1-weighted Contrast-enhanced Imaging

 

ACC

Sensitivity

Specificity

Radiomics

72.78%(95% CI: 0.45,0.91)

78.36%(95% CI: 0.56,1.00)

61.33%(95% CI: 0.20,0.82)

Radiologist 1

66.23%(95% CI: 0.55,0.76)

61.50%(95% CI: 0.43,0.78)

68.62%(95% CI: 0.55,0.80)

Radiologist 2

55.84%(95% CI: 0.45,0.66)

69.25%(95% CI: 0.50,0.84)

49.13%(95% CI: 0.36,0.62)

Radiologist 3

55.84%(95% CI: 0.45,0.66)

69.23%(95% CI: 0.50,0.84)

47.06%(95% CI: 0.34,0.61)

Back to article page

BMC Medical Imaging

ISSN: 1471-2342

Contact us