Sentence examples for varying algorithms from inspiring English sources

Does agreement between several and varying algorithms influence clinician decision-making?

In this study, we use variations of four common algorithms for CNV detection (PennCNV, QuantiSNP, HMMSeg, and cnvPartition) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV) to illustrate the effects of varying algorithms and definitions of overlap on CNV discovery.

In this study, we use variations of four common algorithms for CNV detection (PennCNV [8], QuantiSNP [9], HMMSeg [16], and cnvPartition [17]) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV; see Figure 1) to illustrate the effects of varying algorithms and definitions of overlap on CNV identification and discovery.

Using slightly varying algorithms, these programs scan a library of mRNA 3'UTR regions to identify potential binding sites for the miRNAs of interest.

This unwillingness is in part driven by varying algorithms with regard to diagnostic and treatment strategies, fear of potential malpractice liability, and/or anxiety of the patient.

In CVD hospitalised patients (2000 05), under-identification was greater in urban residents, older people and socially more advantaged Indigenous people, with varying algorithms giving different estimates of under-count.

We address this issue by considering MU detectors and channel estimators, with varying algorithm complexity.

"While we find it disappointing that the author has made no attempt to test for robustness of the proposed new approach by examining the stability of results under varying algorithm choices and parameters, the revised manuscript now includes an appropriate disclaimer".

Figure 9 shows the performance of the transmitter using PBAP learning algorithm in the upper part and fictitious play in the bottom part, for varying learning algorithms of the jammer.

To date, the limited number of machine learning studies on resting state EEG in depression have used varying classification algorithms and have been found to classify MDD patients and healthy controls with an overall accuracy ranging between 60 90 % [ 31– 31].

This paper presents a novel, non-parametric, linear parameter varying (LPV) algorithm for identification of linear time-varying systems.