Malignancy in Ground-Glass Opacity Using Multivariate Regression and Deep Learning Models: A Proof-of-Concept Study.

Subsequently, a univariate analysis was performed in order to find texture variables with statistical significance ( p -value < 0.05) or near significance (0.05 < p -value < 0.1) that are able to distinguish between CT scans with GGO lesions characterized as either malignant or benign.

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p < 0.1 was considered a statistical trend (‘near-significant’) given the exploratory nature of this analysis.

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Using the multivariate statistical regression, we identified 19 variables with statistically significant or near-significant differences through univariate analysis.

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