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Table 4 Comparison of DaTscan image feature extraction methods

From: A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson’s disease

Method

MAPE

MAE

MSE

r

R2

Ensemble approach

18.36%

(11.74%, 24.98%)

4.70

(3.56, 5.84)

34.53

(18.81, 50.25)

0.84

0.71

DaTscan + Semi-quantitative + All ImageNet

19.64%

(12.09%, 27.18%)

4.79

(3.65, 5.94)

35.48

(20.11, 50.85)

0.82

0.67

DaTscan + Semi-quantitative

18.82%

(11.32%, 26.31%)

4.74

(3.36, 6.12)

40.60

(14.59, 66.60)

0.79

0.62

DaTscan + All ImageNet

20.64%

(11.50%, 29.79%)

4.81

(3.45, 6.18)

40.95

(19.94, 61.96)

0.79

0.63

Semi-quantitative + All ImageNet

18.82%

(12.75%, 24.89%)

4.83

(3.69, 5.96)

35.57

(20.41, 50.73)

0.82

0.67

DaTscan

19.89%

(12.48%, 27.30%)

5.04

(3.78, 6.29)

40.41

(22.09, 58.74)

0.81

0.66

Semi-quantitative

21.43%

(13.76%, 29.09%)

5.58

(4.13, 7.03)

51.29

(27.25, 75.33)

0.76

0.57

All ImageNet

20.18%

(13.76%, 26.59%)

5.15

(3.90, 6.40)

41.44

(20.15, 62.72)

0.78

0.62

VGG16

21.67%

(13.99%, 29.35%)

5.54

(4.14, 6.94)

49.31

(26.95, 71.67)

0.75

0.56

ResNet50

19.70%

(13.82%, 25.58%)

5.32

(4.03, 6.61)

44.14

(25.64, 62.65)

0.79

0.62

DenseNet121

20.24%

(13.04%, 27.45%)

5.23

(3.90, 6.56)

44.12

(23.23, 65.01)

0.79

0.63

InceptionV3

21.89%

(14.30%, 29.48%)

5.47

(4.17, 6.76)

45.89

(25.32, 66.46)

0.76

0.58

  1. Data in parentheses are 95% confidence intervals
  2. All values for r were significant (P < 0.001)
  3. MAPE, mean absolute percentage error; MAE, mean absolute error; MSE, mean squared error; r, Pearson correlation coefficient; R2, coefficient of determination