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In this paper, we proposed a method achieving a better performance as shown in Table 5.
Evans and Yousif [30] presented an unconditionally stable second-order accurate finite difference scheme using the alternating group explicit method achieving a better accuracy level.
The combination of RCDzyme signal amplification and proximalis zero-background signal remarkably improves the sensitivity of this method, achieving a dynamic range of two orders of magnitude and giving a detection limit down to 86 pM, which is much lower than those of related literature reports.
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The performances are better when we go to k = 30 folds, with the LP method achieving an accuracy of 0.64 and an MCC value of 0.28.
Our method achieves a ranging from to.
That method achieved a 100%% accuracy with LS_SVM_1vs1.
Compared to the rank method, the prime method achieves a higher provenance compression ratio.
Specifically, the HO Comp method achieved a 33.1%% of improvement compared to the Tilt Comp method.
This method achieved a sensitivity of 100% and a false detection rate of 0.16/h.
Test results show that the proposed method achieves a more accurate forecast.
The proposed method achieves a good result both on noise suppressing and image reconstruction.
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