“…Least squares support vector machine had the highest accuracy (99%), while the K-nearest neighbor algorithm had the highest sensitivity (98%) and specificity (98%). Quadric discriminant analysis achieved the lowest accuracy (91%), sensitivity (89%), and specificity (89%). …”
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“…Factors of bacterial genera were extracted utilizing factor analysis with varimax rotation and factors univariately associated with FGID or SR-NCWS included in a subsequent multivariate analysis of variance to identify statistically independent discriminators. Anxiety scores (p < .05) and increased symptom responses to a nutrient challenge (p < .05) were univariately associated with FGID. …”
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“…Receiver operating characteristic curves were used to determine the threshold with pHF and pHI that best discriminated between UpH >5.75 and ≤5.75 compared with pHP, and area under the curve (AUC) was used to assess the accuracy. …”
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“…Our case draws attention to the fact that biopsy results are necessary in discriminating between the two entities, due to the diagnostic conundrum in context of Anterior Hypopituitarism. …”
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“…Binary logistic regression analysis and receiver operator characteristic (ROC) curves were applied to discriminate and assess the predictive parameters. RESULTS: A total of 129 AS patients were divided into Fracture group (41 cases) and Non‐fracture group (88 cases) based on whether CSF existed. …”
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“…Dynamic comparisons of the bacterial composition at baseline, 6 weeks, and 12 weeks showed that the abundance of Weissella significantly increased in the R group at 6 weeks and the abundance of Fusobacterium and Anaerotruncus significantly increased in the NR group at 12 weeks. Linear discriminant analysis effect size analysis indicated that bacteria of Bacteroidetes, especially Bacteroides, were enriched in the NAE group, whereas flora of Firmcutes, such as Faecalibacterium prausnitzii, Bacteroides fragilis, and Ruminococcus lactaris, were enriched in the AE group. …”
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“…Partial least squares-discriminant analysis (PLS-DA) multivariate statistical analysis showed that volatile flavor compounds could be used as the most ideal indicators for tracing the source of hairtail. …”
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“…Abundances of the genus Methanobrevibacter and total methanogens were reduced (P = 0.050 and P = 0.016) by red seaweed extract supplementation. The linear discriminant analysis effect size (P < 0.05, LDA ≥ 2.0) showed that UG Succinivibrionaceae, Anaeroplasma, and UG Ruminococcaceae, which are associated with higher propionate production, starch degradation, and amylase activity were relatively more abundant in red seaweed extracts than in the CON. …”
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“…Principal coordinate analysis (PCoA) showed different clustering according to the pregnancy status. Linear discriminant analysis effect size (LEfSe) revealed that the microbial species in group N that were significantly different from those of other groups were concentrated in the genus Neisseria. …”
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“…Results: 1,409 features were extracted and reduced to 13 features as the optimal discriminators to build the radiomics model. In the validation set, ROC curves revealed that the LR classifier had the best predictive performance, with an area under the curve (AUC) of 0.831 in DM, 0.883 in MIC, and 0.904 in the N group, compared with the SVM and KNN classifiers. …”
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“…For both FFC and NB scales, the construct validity was assessed through exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and convergent and discriminant validity, the internal consistency was evaluated using the Cronbach's alpha coefficient, McDonald's omega (Ω) and Theta coefficient (θ), as well as the stability was assessed via intraclass correlation coefficient (ICC). …”
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“…To demonstrate the prowess of the discriminator and to bring some explainability to the working of our ensemble, we have used Uniform Manifold Approximation and Projection to plot the latent-space vectors for the dangerous and non-dangerous objects of the test-set; this analysis indicates that the Ensemble learns better features for separating the anomalous class from non-anomalous with respect to the individual architectures. …”
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“…Furthermore, these techniques cannot discriminate whether the damage is due to oxidative stress. …”
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“…The variables that significantly discriminated MV from non-MV patients in univariate analysis were entered into a multiple stepwise logistic regression analysis. …”
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“…PURPOSE: To identify foot and shank coordination patterns that discriminate among individuals with CAI, copers, and healthy controls and to investigate whether copers display a different strategy to overcome altered sensorimotor function after a lateral ankle sprain compared with individuals with CAI and healthy controls. …”
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“…The machine learning pipeline identified two biomarker combinations that accurately distinguished patients with SLE from controls and discriminated between active and inactive SLE. The validated results of ELISAs for two biomarker combinations were in line with the discovery cohort results. …”
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“…DISCUSSION: Microorganisms residing within the gut of the patients at hospital admission, were able to significantly discriminate the clinical evolution of COVID-19 patients, in particular who will develop mild or severe respiratory involvement. …”
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“…Cytology had 96.8% sensitivity and 90.3% specificity to discriminate positive/negative patients compared to H&E (p = 0.004), and 87.3% sensitivity and 89% specificity when compared to OSNA (p = 0.56). …”
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“…Among regional LSN scores, ROI(5) showed the highest AUROC (0.871 at cut‐off 1.12) for discriminating F(0‐2) vs. F(3‐4) and the best correlation with mean LSN score (r = 0.800, −0.07 limit of agreement). …”
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“…CONCLUSIONS: This is the first example in TETs that deep learning can discriminate between TET histologic subtypes using digital H&E slides. …”
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