Sentence examples for predictions and different from inspiring English sources

The simulation framework and evaluation is detailed in the Additional file 1. Figure 1 shows sensitivity, specificity and F-measure (representing the overall prediction accuracy) for the single method gene predictions and different combinations generated by IPred.

10-Year fatal cardiovascular disease risk prediction by the SCORE score and 10-Year global cardiovascular disease risk prediction by the Reynolds risk score Mean (SD) 10-year cardiovascular disease risk predictions and different risk categories calculated by the SCORE score and the Reynolds risk score are shown in Table  4.

The artificial intelligence models produced reasonable trends for year-round prediction and different operational scenarios.

Numbers of available genetic markers seem to be related to the prediction accuracy, and different numbers of genetic variants were selected to build the disease risk prediction model.

In [16], different approaches to calculate the prediction coefficients and different estimators for calculating the a posteriori speech were investigated.

Using additional protein interaction networks, different miRNA target prediction algorithms, and different expression data sets will likely reveal more miRNAs with high-influence on cancer progression.

Each CU contains different prediction units (PUs), and different prediction modes, i.e., SKIP, merge, inter modes (Inter2N×2N, Inter2N×N, InterN×2N, and InterN×N), asymmetric motion partitioning (AMP) modes (Inter 2N×nU, Inter 2N×nD, Inter nL×2N, Inter nR×2N), and intra-prediction modes.

It is still unclear, though, exactly how TIMP-1 is related with prognosis and prediction, and whether different information may be obtained from TIMP-1 in different patient subgroups.

With the result comparison between the empirical prediction and five different data mining algorithms, the ANN algorithm shows to be the most accurate for welding operations.

The different SNP panels used for the prediction of DGV and different training and validation populations largely explain these differences.

We evaluated the different prediction scoring systems and different cutoff levels by calculating the sensitivity, specificity and predictive values.