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  1. 73941
    “…Furthermore, we used the identified transcriptional signatures to develop a discriminative classifier for molecular stratification of patients with sicca. …”
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    Plasmacytoid DCs From Patients With Sjögren's Syndrome Are Transcriptionally Primed for Enhanced Pro-inflammatory Cytokine Production
  2. 73942
    “…The optimal radiomic features were chosen using multivariable logistic regression, random forest, support vector machine, X-Gradient boost and decision tree classifiers. Discriminating performance was assessed with area under receiver operating characteristic curve (AUC), accuracy and F-1score. …”
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    CT radiomic features for predicting resectability of oesophageal squamous cell carcinoma as given by feature analysis: a case control study
  3. 73943
    “…In Study 2, we analysed 1391 coronary PVAT radiomic features in 101 patients who experienced major adverse cardiac events (MACE) within 5 years of having a CCTA and 101 matched controls, training and validating a machine learning (random forest) algorithm (fat radiomic profile, FRP) to discriminate cases from controls (C-statistic 0.77 [95%CI: 0.62–0.93] in the external validation set). …”
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    A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography
  4. 73944
    “…Several drugs targeting distinct phases of the cell cycle have been developed but the inability of many of them to discriminate between normal and cancer cells has strongly limited their clinical potential because of their reduced efficacy at the concentrations used to limit adverse side effects. …”
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    Downregulation of class II phosphoinositide 3-kinase PI3K-C2β delays cell division and potentiates the effect of docetaxel on cancer cell growth
  5. 73945
    “…The predictive accuracy and discriminative ability of the inclusive nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. …”
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    An integrated nomogram combining lncRNAs classifier and clinicopathologic factors to predict the recurrence of head and neck squamous cell carcinoma
  6. 73946
    “…Partial least squares discriminant analysis showed a significant difference in the metabolic profile between the fasting and carbohydrate groups, compatible with the endocrine effects of insulin (i.e., increased serum-lactate and pyruvate and decreased ketone bodies and amino acids in the carbohydrate group). …”
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    Metabolic consequences of perioperative oral carbohydrates in breast cancer patients — an explorative study
  7. 73947
    “…Affective and multiple symptom clusters showed a good discriminative ability (C-statistic 0.766; sensitivity 51.2% and specificity 86.7%) for FEP, and many patients in these clusters had consulted for their symptoms several years before FEP diagnosis. …”
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    Patterns of symptoms before a diagnosis of first episode psychosis: a latent class analysis of UK primary care electronic health records
  8. 73948
    “…Samples were cultured to discriminate between the two pathogens. We compared risk factors, symptoms, severity of disease, secondary infections and socio-economic consequences for (i) culture-confirmed Shigella spp. versus culture-confirmed EIEC cases (ii) culture positive versus PCR positive only shigellosis cases. …”
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    Incidence, clinical implications and impact on public health of infections with Shigella spp. and entero-invasive Escherichia coli (EIEC): results of a multicenter cross-sectional study in the Netherlands during 2016–2017
  9. 73949
    “…Composite reliability of 9 constructs ranged from 0.673 to 0.841. The discriminant validity of all constructs met the Fornell and Larcker criteria. …”
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    Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study
  10. 73950
    “…Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort. …”
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    Multi-omic serum biomarkers for prognosis of disease progression in prostate cancer
  11. 73951
    “…The correlations between GGN-vessel relationships and pathology were evaluated, and the diagnostic value of complementary Lung-RADS version 1.1 in discriminating malignant pGGNs were analyzed. RESULTS: The inter-reader agreements for Lung-RADS 1.1 (intraclass correlation coefficient (ICC= 0.999) and complementary Lung-RADS 1.1 (ICC= 0.971) displayed good reliability. …”
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    Effectiveness and Feasibility of Complementary Lung-RADS Version 1.1 in Risk Stratification for pGGN in LDCT Lung Cancer Screening in a Chinese Population
  12. 73952
    “…Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. …”
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    Unsuspected Involvement of Spinal Cord in Alzheimer Disease
  13. 73953
    “…Current immunodiagnostic tests cannot discriminate between latent, active and past TB, nor predict progression of latent infection to active disease. …”
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    Cell-Mediated Immune Responses to in vivo-Expressed and Stage-Specific Mycobacterium tuberculosis Antigens in Latent and Active Tuberculosis Across Different Age Groups
  14. 73954
    “…BACKGROUND: Cerebrospinal fluid biomarker profiles characterized by decreased amyloid-beta peptide levels and increased total and phosphorylated tau levels at threonine 181 (pT181) are currently used to discriminate between Alzheimer’s disease and other neurodegenerative diseases. …”
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    Cerebrospinal fluid phospho-tau T217 outperforms T181 as a biomarker for the differential diagnosis of Alzheimer’s disease and PET amyloid-positive patient identification
  15. 73955
    “…Previously we published results detailing targeted mRNA sequencing (RNA-Seq) on a next generation sequencer using intact RNA derived from freshly frozen rat liver tissues. We successfully discriminated genotoxic hepatocarcinogens (GTHCs) from non-genotoxic hepatocarcinogens (NGTHCs) using 11 selected marker genes. …”
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    Using FFPE RNA-Seq with 12 marker genes to evaluate genotoxic and non-genotoxic rat hepatocarcinogens
  16. 73956
    “…Elastography is a useful tool for discriminating benign and malignant thyroid nodules. The aim of this study is to investigate the diagnostic efficiency of elastography for high-suspicion thyroid nodules based on the 2015 ATA guidelines in the Chinese population. …”
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    Elastography for the diagnosis of high-suspicion thyroid nodules based on the 2015 American Thyroid Association guidelines: a multicenter study
  17. 73957
    “…We demonstrated our methods have better classification capability when comparing with conventional methods including Fisher linear discriminant (FLD), K-nearest neighborhood (KNN), linear support vector machines (linSVM) and radial basis function based support vector machines (rbfSVM). …”
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    Method of regulatory network that can explore protein regulations for disease classification
  18. 73958
    “…CONCLUSIONS: The combination of multi-parametric MRI and machine learning significantly improved the discriminating ability of viable cartilaginous tumour components. …”
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    Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study
  19. 73959
    “…Besides, nucleosomes displayed potential as a biomarker for discriminate patients according to disease activity. …”
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    Enhanced NETosis generation in radiographic axial spondyloarthritis: utility as biomarker for disease activity and anti-TNF-α therapy effectiveness
  20. 73960
    “…Best feature subsets were selected by Pearson correlation coefficient and recursive feature elimination, whereupon a radiomics classifier was built with SVM. The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). …”
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    Differentiation of Treatment-Related Effects from Glioma Recurrence Using Machine Learning Classifiers Based Upon Pre-and Post-Contrast T1WI and T2 FLAIR Subtraction Features: A Two-Center Study
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