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1  assessed intersubject (4 donors) as well as intrasubject (3 different blood samples from 1 donor) va
2 ues ranging from 0.3 to 0.8, showed the best intrasubject and intersubject variability and reliabilit
3                                          All intrasubject and three of six intersubject section presc
4                                        On an intrasubject basis, short IAA exposures of 0.6 min separ
5                                          The intrasubject CC for AAL-derived regions was high (0.91 +
6  was assessed by repeatability coefficients, intrasubject coefficients of variation (CV), and confide
7 pose of this study was to obtain continuous, intrasubject controlled assessment of the relationship b
8 n mean number of defects per section (median intrasubject correlation [r(m)] = 0.01, P = .64) or chan
9               First, using a time-warp based intrasubject correlation method, we identified all areas
10                  R2* mapping had the highest intrasubject correlations with iron in subcortical gray
11 lity assurance and analysis of data improved intrasubject CV from 15.9% to 10.7% for averaged SUV(max
12                            For SUV(max), the intrasubject CV varied from 10.7% to 12.8% for the QA mu
13                                          The intrasubject CV was 3.9% for TEE(DLW) and 9.9% for MEI.
14 ty differences were not found in analysis of intrasubject data.
15 ) states and high SI states using a powerful intrasubject design, as well as an intersubject case-cas
16                                              Intrasubject differences in the total body and subcompar
17 bility analyses that explicitly accounts for intrasubject fluctuations (e.g., due to measurement nois
18 tive by dominance epistasis, and account for intrasubject fluctuations due to individuals with repeat
19                                              Intrasubject genetic distance and entropy were highest i
20 e matched pairing was shown by PET and SPECT intrasubject imaging to have nearly identical targeting
21  26 study subjects, 19 showed no evidence of intrasubject K1 sequence variability, but, in 7 subjects
22                                     Distinct intrasubject lineages (ISLs) were defined as MRSA genome
23 n of within-subject standard deviation (Sw), intrasubject precision (1.96xSw), coefficient of variati
24                                              Intrasubject precision of baseline measurements was asse
25                   Methods: An intermodal and intrasubject registration with normalized mutual informa
26                                              Intrasubject regression revealed a distributed network o
27                                              Intrasubject repeatability of epithelial indices was ass
28 e concordance correlation coefficient (CCC); intrasubject repeatability was measured using the coeffi
29  PET emission data but with MR-AC from these intrasubject repeated attenuation maps.
30                                          The intrasubject reproducibility for the patients improved w
31       Control subjects showed overall higher intrasubject reproducibility of brain activation pattern
32                                          The intrasubject reproducibility of the brain activation pat
33  the same subjects, to investigate potential intrasubject sequence differences.
34               Moreover, a significantly high intrasubject similarity between avalanche size and durat
35 ly, within each subject, three corresponding intrasubject studies were fitted simultaneously to a sin
36 during filgrastim treatment contained unique intrasubject subclusters that shared a most recent commo
37                                         Mean intrasubject test-retest variability for cortical averag
38 ed this approach, examining intersubject and intrasubject variability and the validity of using a sin
39 od to be a consequence of the atypically low intrasubject variability in blood SUV and uptake time an
40                         Group differences in intrasubject variability in reaction time were examined,
41 ical associations with severity, course, and intrasubject variability of depressive symptoms.
42              Sample stability and inter- and intrasubject variability were evaluated in the urine of
43 red separate scans with the drawback of high intrasubject variability.
44  occasions and the other taking into account intrasubject variability.
45 ) when responding to positive stimuli and an intrasubject variable (mood) when responding to negative
46 nal measures, namely trajectory and mean and intrasubject variance over time.
47 ole and had a lower dynamic range and higher intrasubject variance.
48 e classification by comparing the inter- and intrasubject variation of urinary phthalate metabolite l
49 demonstrated high temporal stability (or low intrasubject variation) over the entire study period, th
50 etest reliability was evaluated by comparing intrasubject visual read ratings and SUVrs for 2 PET ima