“…RESULTS: The algorithm was validated on data of 41 participants, including 26 men and 15 women with a mean age of 53 (SD 13) years, BMI of 30 (SD 7), AHI of 27 (SD 31) events/hour, and sleep duration of 5 (SD 1) hours; 20 participants had positional sleep apnea, 15 participants had nonpositional sleep apnea, and the positional status could not be discriminated for the remaining 6 participants. AHI values estimated by the 3D-CNN model correlated strongly and significantly with the gold standard (Spearman correlation coefficient 0.79, P<.001). …”
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“…Then, a prognostic nomogram incorporating the serum iron level, T stage and N stage was developed for individualized prognosis predictions. It had good discriminative ability with a C-index of DFS (0.729; 95% CI 0.666–0.792) and OS (0.739; 95% CI 0.666–0.812), respectively. …”
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“…In addition, 39 metabolites were identified as important variables to contribute to the classifications using an orthogonal partial least squares-discriminant analysis (OPLS-DA) (VIP > 1) and also significantly different between healthy and AD-diagnosed individuals using univariate analysis (p-value < 0.05 and false discovery rate < 0.05). …”
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“…The predictive accuracy and discriminative ability were measured by calibration plots, concordance index (C-index), and risk group stratification. …”
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“…Moreover miRNA 9-3p and endocan performed better than α-fetoprotein in discriminating HCC patients from cirrhosis and healthy patients. …”
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“…The differences between hVISA and VSSA were maximized by orthogonal partial least squares discriminant analysis (OPLS-DA) and the affected metabolic pathways were identified with MetaboAnalyst. …”
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“…We implemented a two-step testing algorithm to discriminate true CDI from colonization then evaluated the effect on rate of HO CDI and oral vancomycin. …”
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“…The most reported machine learning (ML) algorithms used for classification were linear discriminant analysis (LDA) (48.64%) and support vector machine (16.21%), while only one study used a deep learning algorithm: a Convolutional Neural Network (CNN). …”
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“…The results suggest that using both the mip and rpoB genes makes it possible to correctly discriminate between several species, allowing possible new species to be identified, as confirmed by preliminary whole-genome sequencing analyses performed on our isolates. …”
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“…The results showed that the 8-factor model was the best solution (chi-square/df = 2.41, CFI = .98, TLI = .97, RMSEA = .06). The discriminant and convergent validity of the SHAT-PS were evaluated as satisfactory and the scale had high internal consistency (Cronbach’s alpha for all subscales > .93). …”
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“…Both selections contained the same single amino acid substitution, from alanine to valine at position 205 (A(205)V) in the AHAS1 protein, and KASP™ markers were developed to discriminate between tolerant and intolerant genotypes. …”
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“…RESULTS: Principal component analysis and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) based on lipid metabolomics analysis showed a clear distribution in different regions. …”
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“…OBJECTIVE: This study was conducted in order to investigate the feasibility of using radiomics analysis (RA) with machine learning algorithms based on breast magnetic resonance (MR) images for discriminating malignant from benign MR-detected additional lesions in patients with primary breast cancer. …”
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“…The SAPS II scoring system had a better discriminative performance of 90-day mortality and 1-year mortality in post-cardiac surgery patients than the SOFA scoring system. …”
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“…The front keratometry mean (ΔFKmean) and standard deviation (ΔFKsd) and the front elevation standard deviation (ΔFEsd) and maximal (ΔFEmax) values within a 1.5-mm radius of the bilateral differential topography yielded the four highest accuracies (area under the ROC curve = 0.985, 0.985, 0.984, and 0.983, respectively) for discriminating KC cases (including FFK cases) from normal cases. …”
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“…Moreover, MRI-derived measures have had limited success to date discriminating between FTLD-Tau or FTLD-TDP. T(2)*-weighted (T2*w) ex vivo MRI has previously been shown to be sensitive to non-heme iron in healthy intracortical lamination and myelin, and to pathological iron deposits in amyloid-beta plaques and activated microglia in Alzheimer’s disease neuropathologic change (ADNC). …”
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“…The presence of three main clusters is also clearly reflected in the discriminant analysis of principal components (DAPC) based on the microsatellite marker analyses. …”
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“…The differential metabolites were evaluated by multivariate analysis, and Bayes discriminant analysis and receiver operator characteristic (ROC) analysis were used to discover potential diagnostic or therapeutic biomarkers. …”
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“…In logistic regression models, arithmetic combinations of RTF values [e.g., (RTF-Alpha) + (RTF-Beta)/(RTF-Delta + RTF-Theta)] and RTF-Alpha values at occipital or parietal locations are most able to discriminate between PD and controls. A principal component (PC) from principal component analysis (PCA) using RTF-band values in all subjects is associated with PD status (p = 0.004, β = 0.31, AUC = 0.780). …”
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“…ADC showed a strong negative correlation with Gleason score (r = −0.77), and the highest discriminative ability for detection and localization of CSPCa (area under curve [AUC]: 0.91), followed by K(trans) (r = 0.74; AUC: 0.89), PI-RADS (0.73; 0.86), SUVmax ratio (0.49; 0.74), and K(ep) (0.24; 0.66). …”
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