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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 s with biopsy-proven sAH (modified Maddrey's discriminant function 32, Model for End-Stage Liver Dise
7 the state-of-the-art, which is featured by a discriminant function algorithm developed very recently
8 the current velocity of this change and used discriminant function analyses to classify watershed vul
9                                              Discriminant function analyses using local volume measur
10                      Principal component and discriminant function analyses were applied to accelerat
11                      Forward stepwise linear discriminant function analyses were used to examine the
12 as examined by using multiple regression and discriminant function analyses.
13   The multivariate statistical techniques of discriminant function analysis (DFA) and hierarchical cl
14 ensor array were processed using a canonical discriminant function analysis (DFA) pattern recognition
15                                      We used discriminant function analysis (DFA) to evaluate how wel
16 ver operating characteristic (ROC) analysis, discriminant function analysis (DFA), leave-one-out cros
17 e used to perform a stepwise cross-validated discriminant function analysis (DFA).
18 IR spectra for multi-class identification by discriminant function analysis (DFA).
19 g community structure was demonstrated using discriminant function analysis (DFA, selecting taxa that
20                          Principal component-discriminant function analysis (PC-DFA) allowed the diff
21 omponent analysis (PCA), principal component-discriminant function analysis (PC-DFA) and partial leas
22 assification accuracy compared to a permuted discriminant function analysis (pDFA), both for the vale
23                                              Discriminant function analysis allowed identification of
24    It utilizes stepwise multiple regression, discriminant function analysis and logistic regression t
25                                              Discriminant function analysis based on left and right t
26          Results of the study indicated that discriminant function analysis emerged as the most effec
27                              A morphological discriminant function analysis failed to provide a good
28                                              Discriminant function analysis identified deficits in su
29                                       Direct discriminant function analysis identified three signific
30                                              Discriminant function analysis indicated that much of th
31                                              Discriminant function analysis of the data showed signif
32                                              Discriminant function analysis optimally identified the
33                                            A discriminant function analysis revealed two prominent di
34        Based on the contamination profile, a discriminant function analysis separated the rough-tooth
35 ve assessment of behavioral measures through discriminant function analysis showed that Tau mice were
36                                            A discriminant function analysis shows separation between
37 iking atrophy patterns) and the results of a discriminant function analysis that incorporated clinica
38 nalysis to identify objective call types and discriminant function analysis to assess context specifi
39 tive data from 384 Chinese children and used discriminant function analysis to determine the best ana
40                                      We used discriminant function analysis to identify the most effi
41                                            A discriminant function analysis using neuropsychological
42 rge ratios (m/z) associated with resistance, discriminant function analysis was employed on spectra d
43                                              Discriminant function analysis was used to create an art
44                                              Discriminant function analysis was used to estimate suit
45                                              Discriminant function analysis was used to examine how a
46                                              Discriminant function analysis was used to explore which
47 tical techniques such as principal component discriminant function analysis, canonical correlation an
48  factor scores as independent variables in a discriminant function analysis, the AGQ scores resulted
49 rowear variables were combined into a single discriminant function analysis, the cast data and origin
50                                              Discriminant function analysis, using the degree of hypo
51 , using in vivo intracellular recordings and discriminant function analysis, we found that the respon
52 stinguished between the groups in a stepwise discriminant function analysis.
53 ival were compared with those of the Maddrey discriminant function and logistic regression models dev
54 hows graphically the values of the canonical discriminant functions and the centroids of the interval
55 can be concluded from the correlations among discriminant functions and variables within each statist
56 ge, the aROC associated with each parameter, discriminant function, and subjective stereophoto grade
57 eased VLCFA levels, but the application of a discriminant function based on all three measurements is
58  profiles of each layer and output values of discriminant functions based on individual indices.
59                                              Discriminant functions based on measurements of lower mo
60 rformance of the parameter with largest AUC, discriminant function Bathija, in analysis 1 (AUC = 0.91
61                                          The discriminant functions classify 100% of the wines, with
62                                   Multimeric discriminant functions combined with individual indices
63          The two groups did not overlap on a discriminant function computed from a model comprising t
64                                          The discriminant function containing maximum ectasia indices
65 g parameters for correct peptide assignment, discriminant function (DF) analysis of these parameters
66 c model used for this purpose is the Maddrey discriminant function (DF).
67 as a combination of both factors in a linear discriminant function did not improve the predictive val
68 entifies arbitrary nonlinear multiparametric discriminant functions directly from experimental data.
69                              The constructed discriminant functions exhibited the best classification
70 aluation Scale "others" subscale entered the discriminant function first.
71  calculated zero-order correlations with the discriminant function for each region, then used a machi
72 prediction algorithm that uses the quadratic discriminant function for multivariate statistical patte
73 .9 to 19.4 +/- 3.7 (P = 0.002) and Maddrey's discriminant function from 74.8 +/- 22.8 to 57.4 +/- 31
74  controlled trials of adults with severe AH (discriminant function >/=32 and/or hepatic encephalopath
75 nts with suspected alcoholic hepatitis and a Discriminant Function >/=32 underwent liver biopsy to co
76 with alcoholic hepatitis (modified Maddrey's discriminant function >32), nine with alcohol-related ci
77 ssification of the Frederick Mikelberg (FSM) discriminant function (hazard ratio [HR] 2.51, 95% confi
78 ltivariate model validation showed very good discriminant function in predicting kidney discard (AUC
79         We explain the implementation of the discriminant functions into a decision tree that constit
80                     The Fourier-based linear discriminant function (LDF Fourier) resulted in a sensit
81 f BMO-MRW and pRNFL parameters with a linear discriminant function (LDF) could further enhance glauco
82 , as well as four previously proposed linear discriminant functions (LDFs) and one LDF developed on t
83  End-Stage Liver Disease [MELD] >20, Maddrey discriminant function [MDF] >32) were randomized to rece
84             When applied to AT carriers, the discriminant function misclassified only one out of 18 A
85                                          The discriminant function model for the NDDI-E included six
86 ntly surpassing legacy models like Maddrey's Discriminant Function, Model for End-Stage Liver Disease
87 ver operating characteristic (ROC) curves of discriminant function, neural network results, and quali
88 se score (r = 0.41, P = 0.006) and Maddrey's discriminant function (r = 0.43, P = 0.004).
89                                              Discriminant function score equations were generated to
90 e alcoholic hepatitis, defined as a modified discriminant function score greater than or equal to 32
91 preset criterion with known distributions of discriminant function scores and probabilities of correc
92 ecognition elements (alpha-MoREs) based on a discriminant function that indicates such regions while
93                          We present a set of discriminant functions that can recognize structural and
94 formation was used in training two quadratic discriminant functions that polyadq uses to evaluate pot
95                            PromH uses linear discriminant functions that take into account conservati
96 f a previously published nuclear morphometry discriminant function to predict disease-free survival i
97 les are then used in a non-parametric linear discriminant function to separate GPCRs from non-GPCRs.
98 rements that may enter into the multivariate discriminant function, use of appropriate statistical me
99                                The quadratic discriminant functions used for building the algorithm w
100 was applied to the AC patients and Maddrey's Discriminant Function was applied to the AH patients.
101                                            A discriminant function was derived with two thirds of the
102                                     A linear discriminant function was developed to identify and comb
103                                    Resulting discriminant functions were applied to 317 MCI cases to
104                                          Two discriminant functions were generated and allowed a sati
105                               Results: Three discriminant functions were identified and defined as ma
106                             Several kinds of discriminant functions were used to separate groups of s
107 together with amino acid type provide a good discriminant function, when combined independently with
108                                   We derived discriminant functions, which have a high predictive abi

 
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