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To our knowledge, this is the first time that such a general spatial multivariate model has been formulated.
However, once a multivariate model has been built and the most important spectral features identified, experimental time could be easily reduced to around 10 mins per sample further increasing high throughput possibilities.
The test BA of multivariate model has smallest deviation also.
The multivariate model has as a result of this changed, but remains similar to the authors' original report.
Next, a full multivariate model has been developed that incorporates all the factors, which have survived from the boosting approach and clinic variables based on their statistical or clinical significance.
Recently, a multivariate model has been developed that takes information from the Nottingham grade, ER and PR immunohistochemistry results, HER2 status, tumor size and Ki67 expression to predict the recurrence score category [ 12].
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In the Cox multivariate model, having chronic obstructive pulmonary disease (adjusted HR = 5.25, 95% CI, 2.60 to 10.62) and having hypertension (adjusted HR = 4.31, 95% CI, 1.90 to 9.78) were independent risk factors associated with death from any cause (Table 7 and Table S2).
The final multivariate model had an R of 0.88.
The multivariate model had a high discriminatory power (CPE=0.73, 95% CI 0.70 0.76).
However, this multivariate model had low predictive accuracy (area under the ROC curve, 0.68).
The multivariate model had 33 cases with missing values, leaving data from 243 persons for the multivariate model.
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