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We exploited the potential of features extracted automatically from images and investigated the diagnostic value of each feature by applying the support vector machine recursive feature elimination algorithm.
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This study confirms the potential of feature selection techniques for GRN inference.
The problem is especially acute when sample sizes are very small and the potential number of features is very large.
Artificial exposures are good field sites for learning because of their accessibility, and the potential range of features they present for first-hand examination.
Furthermore, especially multi-resolution decomposition produces an important loss on the potential interpretation of features and signals, regardless of the remarkable increase of the statistical significance of the features reported using such analyses.
Hence, blindly chosen fixed-field-views that lead to the potential omission of features of interest or low-resolution data of whole objects lacking cellular detail cannot fulfill this need.
In addition, we show the potential of these features to characterise and classify between network topologies.
Two prostate studies have shown the potential of fractal features in distinguishing between benign and malignant disease with histological confirmation [21, 49].
The goal of our experiments was to evaluate the potential of selected features for automatic measurement of the impairment cognition through prosodic analysis.
When nanoroughened surfaces are utilized, the use of capture antibodies is not necessary, showing the potential of nanoscale features to capture a metamorphic population of cells.
Therefore, the bias caused by the classification scheme could be largely ameliorated and the diagnostic potential of the features could be ascertained through extensive experiments.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com