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Table 2 Three input variables analyses and 5 × 2 cross-validation protocol (average results obtained in 10 analyses with each model). LDA: Linear Discriminant Analysis, No: Number; SD: Standard Deviation.

From: Artificial neural networks allow the use of simultaneous measurements of Alzheimer Disease markers for early detection of the disease

MODELS

No.

Senitivity

Specificity

Mean Accuracy

No. Errors

SD Mean Accuracy

p

SelfDASn

10

94,03%

92,12%

93,08%

2,1

2,98

0,000036

TasmDASn

10

95,12%

90,51%

92,82%

2,1

3,26

0,000016

TasmSASn

10

92,51%

91,99%

92,25%

2,4

2,67

0,000022

SelfSASn

10

94,50%

89,87%

92,19%

2,3

2,58

0,000020

TasmDABm

10

93,54%

88,91%

91,23%

2,6

2,84

0,000007

TasmDABp

10

93,51%

88,91%

91,21%

2,6

3,20

0,000001

SelfSABm

10

93,57%

88,14%

90,86%

2,7

3,76

0,000144

SelfDABp

10

92,43%

88,14%

90,29%

2,9

3,35

0,000031

TasmSABp

10

90,79%

88,98%

89,88%

3,1

3,14

0,000302

SelfDABm

10

91,34%

88,21%

89,78%

3,1

4,02

0,000398

TasmSABm

10

91,90%

87,37%

89,64%

3,1

4,07

0,000504

SelfSABp

10

90,29%

88,91%

89,60%

3,2

2,96

0,000311

FF_Sn

10

91,90%

84,17%

88,03%

3,5

4,11

0,000734

FF_Bm

10

88,63%

86,54%

87,58%

3,8

3,61

0,000860

FF_Bp

10

88,63%

85,77%

87,20%

3,9

3,72

0,001092

SMDA

10

89,71%

78,65%

84,18%

4,6

6,31

0,021734

LDA

10

90,26%

72,95%

81,61%

5,2

5,47

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