METHOD:We performed a retrospective study of a cohort of 150 patients transplanted and discharged from Duke University Hospital between January 2015 and September 2016.
To evaluate the predictive performance of the classification method, we performed a cross-validation experiment using the gold standard compound protein interaction data.
To assess the performance of the consensus module detection method, we performed a simulation study involving two simulated gene expression data sets.
In order to evaluate the classification performance of the proposed pathway activity inference method, we performed the following cross-validation experiments.
In order to assess the sensitivity of our method we performed two independent experiments.
To test the robustness of the method we performed a larger-scale reaction to give 3.4 grams of product.
Method: We performed a systematic review, examining reasons reported in more than forty primary studies.
We also provide the segmentation results overlaid on the input image in Supplementary Fig. 4. To further evaluate the method, we performed a second experiment segmenting cell nuclei from non-nuclei markers.
To demonstrate the effectiveness of our method, we performed computer simulations and experiments using measurements of speeches nixed in an actual environment.
In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature.
Material and Method: We performed the evaluation of 173 Brazilian web sites, which were obtained from four search engines (Google, Yahoo, AltaVista and Radar Uol).
