LitCovid-sentences  

PMC:7160614 / 11250-13828 JSONTXT 12 Projects

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Id Subject Object Predicate Lexical cue
T92 0-295 Sentence denotes To develop an optimal model, we evaluated 3 models by analyzing (i) the clinical features model (C model), (ii) radiological semantic features model (R model), and (iii) the combination of clinical and radiological semantic features model (CR model) by multivariate logistic regression analysis.
T93 296-425 Sentence denotes The classification performances of the models were evaluated by the area under the receiver operating characteristic (ROC) curve.
T94 426-518 Sentence denotes The area under the curve (AUC), accuracy, sensitivity, and specificity were also calculated.
T95 519-720 Sentence denotes A decision curve analysis was conducted to determine the clinical usefulness of the diagnostic model by quantifying the net benefits at different threshold probabilities in the validation dataset [24].
T96 721-800 Sentence denotes The development of decision curve was described in the Supplementary Materials.
T97 801-882 Sentence denotes Figure 2 depicts the flowchart of the proposed analysis pipeline described above.
T98 883-1087 Sentence denotes We also built a nomogram, which was a quantitative tool to predict the individual probability of infection by COVID-19, based on the multivariate logistic analysis of the CR model with the primary cohort.
T99 1088-1244 Sentence denotes Depending on the coefficient of the predictive factors in multivariate logistic regression model, all values of each predictive factor were assigned points.
T100 1245-1324 Sentence denotes A total point was obtained by summing all the points of each predictive factor.
T101 1325-1435 Sentence denotes The scale also showed the relationship between the total point and the prediction probability in the nomogram.
T102 1436-1583 Sentence denotes The corresponding calibration curves of the CR model in the primary cohort and validation cohort are shown in the Supplementary Material (Fig. E3).
T103 1584-1643 Sentence denotes Fig. 2 Workflow of data process and analysis in this study.
T104 1644-1774 Sentence denotes Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section.
T105 1775-1867 Sentence denotes The clinical manifestation and laboratory parameters are provided by electronic case system.
T106 1868-1982 Sentence denotes Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients.
T107 1983-2160 Sentence denotes Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p < 0.05 in statistical analysis.
T108 2161-2257 Sentence denotes Three models based on the selected features are established by multivariate logistic regression.
T109 2258-2400 Sentence denotes These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model).
T110 2401-2578 Sentence denotes The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively