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In Chen's report [ 11], AAP propensity scale was used in combination with a support vector machine (SVM) to construct a model which achieved optimal accuracy of 71.09% on Chen872 using fivefold cross-validation at window size 20.
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Finding a model which achieves this will not be easy.
Legendre and Gautheret [ 16] developed the ERPIN program based on a probabilistic hidden Markov model, which achieved a prediction specificity of 69 to 85% for a sensitivity of 56%.
However, this did not appear to be a problem for the treosulfan with gemcitabine model, which achieved a high degree of correlation despite the presence of a very resistant tumour.
This was provided by the rsv model, which achieved a 30 fold reduction in associations between unlinked markers, leaving high LD values only between pairs of genetically linked SNP loci.
The model which achieved the lowest average error corresponds to a shear beam with lumped mass at the mid-span equal to half the total mass on the diaphragm.
The basic idea of the majority of them is to introduce an integrated model which achieves an optimal common set of weights (CSW).
In this paper, a suboptimal yet a simple and efficient system model, which achieves a better trade-off among the hardware cost, complexity, and the performance, is proposed and analyzed for dual-hop MIMO amplify-and-forward (AF) relay networks.
Then, we construct two diversified similarity neighborhood regularization terms and systemically integrate them into a matrix factorization model, which achieves the knowledge transfer of geographical neighborhoods in improving QoS prediction accuracy.
We present a scalable dissipative particle dynamics simulation code, fully implemented on the Graphics Processing Units (GPUs) using a hybrid CUDA/MPI programming model, which achieves 10 30 times speedup on a single GPU over 16 CPU cores and almost linear weak scaling across a thousand nodes.
The approach automatically learned nonlinear relationships between features and outcomes to generate predictive models, which achieved AUC = 0.7879 performance with a sensitivity of 63.64% and a specificity of 74.19% in the testing data set of 33 women with breast cancer and 31 healthy women controls.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com