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By the risk table, MDR can predict disease risk and will select the SNP combination with the highest prediction accuracy.
The list of target candidate proteins and the associated information (e.g., molecular functions, biological pathways, applicable diseases) are shown with a ranking from the highest prediction score.
Analytical results show that the ensemble technique combining two or more models obtained the highest prediction performance.
Comparison with the well-known existing model shows that the new model has the highest prediction accuracy.
Compared to other prediction models (e.g., simple indicators-based models and Pavement ME Design models), the developed models have the highest prediction accuracy.
For location prediction application, the highest prediction efficiencies of the traditional method on Alwar and Mussourie was only 13%and8%8% respectively as compared to the proposed method.
For major road, ANFIS model A4 gives the highest prediction rate.
The highest prediction power was obtained for models with dimension 35*35.
Another optimum landslide susceptibility map with the highest prediction accuracy was also selected from a limited number of landslide factors.
Also, it can be noted that the highest prediction among all procedures analyzed is achieved by the QuBiLS-MIDAS models.
ROC analysis revealed that ICG-PDR had the highest prediction of 28-day mortality, followed by arterial serum lactate and SOFA (Table 3).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com