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Table 3 Confidence intervals of model performance

From: Enhancing magnetic resonance imaging-driven Alzheimer’s disease classification performance using generative adversarial learning

 

1.5 T

3 T*

3 T* − 1.5 T

(a)

 ADNI test

[0.8968, 0.9172]

[0.9304, 0.9336]

[0.0203, 0.0297]

 AIBL

[0.9258, 0.9422]

[0.9373, 0.9427]

[0.0021, 0.0097]

 NACC

[0.8590, 0.8810]

[0.9058, 0.9082]

[0.0314, 0.0412]

(b)

 ADNI test

[0.9022, 0.9218]

[0.9324, 0.9356]

[0.0175, 0.0265]

 AIBL

[0.7347, 0.7833]

[0.7467, 0.7593]

[−0.0170, 0.0051]

 NACC

[0.8268, 0.8512]

[0.8768, 0.8792]

[0.0334, 0.0443]

  1. (a) 95% confidence intervals of the SS curves for 1.5-T-based model, 3-T*-based model, and difference of AUCs between 3-T* and 1.5-T-based models. (b) 95% confidence intervals of PR curves for 1.5-T-based model, 3-T*-based model and difference of AUCs between 3-T* and 1.5-T-based models
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Alzheimer's Research & Therapy

ISSN: 1758-9193