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Secondly, using the modelled-PCM concentrations lead to improved spatial prediction, as a model containing the modelled-PCM concentrations surpassed the model without the modelled-PCM concentrations, with RMSPEs of 0.257 and 0.276 respectively, which is an increase of 7%.
In this study, using cancer outcome prediction as a model, we wished to test the hypothesis that routinely collected digital health data, if analysed by MLT, could be used to assist conventional tools in predicting clinical outcomes.
2 11 12 In this study, using cancer outcome prediction as a model, we wished to test the hypothesis that routinely collected digital health data, if analysed by state-of-the-art, validated, MLT could be used to assist conventional tools in predicting clinical outcomes.
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We use a characterized source model proposed by Irikura and Miyake (2001), which is one of the most reliable approaches for broadband strong ground motion prediction, as a source model for strong ground motion simulation.
When the height of spruce seedling is 1 3 m and the basal area of overstorey birches is less than 20 m2/ha, our model gives fairly similar predictions as an earlier model (Mielikäinen and Valkonen 1995) for two-storied spruce-birch stands.
With the development of suboptimal structure prediction, a model as versatile as vsfold5 can study these energy differences more closely.
Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes.
In addition, we performed a protein-protein interaction network characterization of the gene products of our positive predictions using Saccharomyces cerevisiae as a model, which revealed a highly connected and modular topology, suggesting a functional association.
The use of this value as a model prediction for all compounds gave an RMSE = 65.7 °C, which can be used as the null hypothesis for MP prediction.
If the model is acceptable, the estimated fluxes are also acceptable as a model prediction.
In principle, every quantity which can be computed based on the model can serve as a model prediction z.
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