ライフサイエンスコーパス: discriminant function

1 gnosis can be controlled via a cost-adjusted discriminant function.

2 compared with Pugh score, MELD and Maddrey's discriminant-function.

3 e (CSLO) parameter, and previously described discriminant functions.

4 5% (0.88 and 0.87, respectively), SLP linear discriminant function (0.79 and 0.81, respectively), and

5 ICU admission, but oxygen saturation and the discriminant function 2 could detect differences 48 hrs

6 the state-of-the-art, which is featured by a discriminant function algorithm developed very recently

7 Discriminant function analyses using local volume measur

8 Forward stepwise linear discriminant function analyses were used to examine the

9 as examined by using multiple regression and discriminant function analyses.

10 The multivariate statistical techniques of discriminant function analysis (DFA) and hierarchical cl

11 ensor array were processed using a canonical discriminant function analysis (DFA) pattern recognition

12 We used discriminant function analysis (DFA) to evaluate how wel

13 ver operating characteristic (ROC) analysis, discriminant function analysis (DFA), leave-one-out cros

14 e used to perform a stepwise cross-validated discriminant function analysis (DFA).

15 IR spectra for multi-class identification by discriminant function analysis (DFA).

16 g community structure was demonstrated using discriminant function analysis (DFA, selecting taxa that

17 Principal component-discriminant function analysis (PC-DFA) allowed the diff

18 omponent analysis (PCA), principal component-discriminant function analysis (PC-DFA) and partial leas

19 Discriminant function analysis allowed identification of

20 Discriminant function analysis based on left and right t

21 A morphological discriminant function analysis failed to provide a good

22 Discriminant function analysis identified deficits in su

23 Direct discriminant function analysis identified three signific

24 Discriminant function analysis indicated that much of th

25 Discriminant function analysis of the data showed signif

26 Discriminant function analysis optimally identified the

27 A discriminant function analysis revealed two prominent di

28 ve assessment of behavioral measures through discriminant function analysis showed that Tau mice were

29 A discriminant function analysis shows separation between

30 iking atrophy patterns) and the results of a discriminant function analysis that incorporated clinica

31 nalysis to identify objective call types and discriminant function analysis to assess context specifi

32 tive data from 384 Chinese children and used discriminant function analysis to determine the best ana

33 We used discriminant function analysis to identify the most effi

34 A discriminant function analysis using neuropsychological

35 rge ratios (m/z) associated with resistance, discriminant function analysis was employed on spectra d

36 Discriminant function analysis was used to create an art

37 Discriminant function analysis was used to estimate suit

38 Discriminant function analysis was used to explore which

39 tical techniques such as principal component discriminant function analysis, canonical correlation an

40 factor scores as independent variables in a discriminant function analysis, the AGQ scores resulted

41 Discriminant function analysis, using the degree of hypo

42 , using in vivo intracellular recordings and discriminant function analysis, we found that the respon

43 stinguished between the groups in a stepwise discriminant function analysis.

44 ival were compared with those of the Maddrey discriminant function and logistic regression models dev

45 hows graphically the values of the canonical discriminant functions and the centroids of the interval

46 can be concluded from the correlations among discriminant functions and variables within each statist

47 ge, the aROC associated with each parameter, discriminant function, and subjective stereophoto grade

48 eased VLCFA levels, but the application of a discriminant function based on all three measurements is

49 profiles of each layer and output values of discriminant functions based on individual indices.

50 Discriminant functions based on measurements of lower mo

51 rformance of the parameter with largest AUC, discriminant function Bathija, in analysis 1 (AUC = 0.91

52 Multimeric discriminant functions combined with individual indices

53 The two groups did not overlap on a discriminant function computed from a model comprising t

54 The discriminant function containing maximum ectasia indices

55 g parameters for correct peptide assignment, discriminant function (DF) analysis of these parameters

56 c model used for this purpose is the Maddrey discriminant function (DF).

57 as a combination of both factors in a linear discriminant function did not improve the predictive val

58 entifies arbitrary nonlinear multiparametric discriminant functions directly from experimental data.

59 aluation Scale "others" subscale entered the discriminant function first.

60 prediction algorithm that uses the quadratic discriminant function for multivariate statistical patte

61 prediction algorithm that uses the quadratic discriminant function for multivariate statistical patte

62 controlled trials of adults with severe AH (discriminant function >/=32 and/or hepatic encephalopath

63 nts with suspected alcoholic hepatitis and a Discriminant Function >/=32 underwent liver biopsy to co

64 with alcoholic hepatitis (modified Maddrey's discriminant function >32), nine with alcohol-related ci

65 ssification of the Frederick Mikelberg (FSM) discriminant function (hazard ratio [HR] 2.51, 95% confi

66 ltivariate model validation showed very good discriminant function in predicting kidney discard (AUC

67 We explain the implementation of the discriminant functions into a decision tree that constit

68 The Fourier-based linear discriminant function (LDF Fourier) resulted in a sensit

69 , as well as four previously proposed linear discriminant functions (LDFs) and one LDF developed on t

70 When applied to AT carriers, the discriminant function misclassified only one out of 18 A

71 The discriminant function model for the NDDI-E included six

72 ver operating characteristic (ROC) curves of discriminant function, neural network results, and quali

73 se score (r = 0.41, P = 0.006) and Maddrey's discriminant function (r = 0.43, P = 0.004).

74 preset criterion with known distributions of discriminant function scores and probabilities of correc

75 ecognition elements (alpha-MoREs) based on a discriminant function that indicates such regions while

76 We present a set of discriminant functions that can recognize structural and

77 formation was used in training two quadratic discriminant functions that polyadq uses to evaluate pot

78 PromH uses linear discriminant functions that take into account conservati

79 f a previously published nuclear morphometry discriminant function to predict disease-free survival i

80 les are then used in a non-parametric linear discriminant function to separate GPCRs from non-GPCRs.

81 rements that may enter into the multivariate discriminant function, use of appropriate statistical me

82 The quadratic discriminant functions used for building the algorithm w

83 A discriminant function was derived with two thirds of the

84 A linear discriminant function was developed to identify and comb

85 Resulting discriminant functions were applied to 317 MCI cases to

86 Several kinds of discriminant functions were used to separate groups of s

87 together with amino acid type provide a good discriminant function, when combined independently with

88 We derived discriminant functions, which have a high predictive abi