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The world of systems engineering methods is changing as rigorous 'off-the-shelf' methods gain popularity.
Both methods gain in noise power reduction in the channel estimation but lose in the asymptotic accuracy.
Risk analysis methods gain more and more acceptance as decision support tools to analyze and reduce risks in engineering applications.
Due to a lower risk of complications, non-invasive monitoring methods gain importance.
Next-generation-sequencing technologies and various other methods gain data from biospecimen, both for translational research and personalized medicine.
Over time, countries will vary in which methods gain or lose shares, while total use in most cases will increase.
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The machine learning methods gained better sensitivities than human doctors at the cost of losing specificities.
Mixed methods gained acceptance amongst researchers in the 1980s, since they addressed epistemological ontological and axiological weaknesses of both the qualitative and quantitative approaches [22].
While these methods gained some popularity in the assessment of treatment effects, their application in side effect assessment is novel.
For this reason gene network inference methods gained considerable interest.
However, the 3 countries took quite different paths for which methods gained in the method mix share and which ones lost, as discussed below.
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