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The binomial regression model for both classifications has shown that, despite normal individuals having been older and presented less FFM, their overweight and obese counterparts were prone to present changes in lipid profile when considering the PBF classification.
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Additionally, several studies into treatment-based classification have shown that people with certain clinical signs and symptoms may exhibit a preferential response to corresponding treatment modalities [ 9- 12].
Recent developments in tumour classification have shown that although the genetic mutations that occur in solid tumours may be heterogeneous and complex, mutations often occur in genes that function in common cell signalling pathways that may render them sensitive to targeted approaches.
Recent studies have criticised the use of Kellgren and Lawrence classification[ 27], while others have shown that measurement of joint space width is reliable and reflects clinical status[ 36].
Experiments have shown that correct classifications are possible even with further reduced signatures, down to 11 genes (data not shown).
However, recent analyses have shown that gene expression-based classifications of mesenchymal subtypes often do not associate with poor survival.
In [14], authors use clustering ensemble for classifiers combination, because the use of cluster analysis techniques in supervised classification tasks has shown that they can enhance the quality of the classification results.
Applying the classification to two cohorts has shown that in some instances it is not possible or indeed plausible to reference a systematic review.
Simultaneously, the analysis has shown that KF classification can be applied in flysch rock mass successfully, together with RMR and GSI classifications.
Using the SVM the reliability problem is treated as a classification approach and extensive numerical experimentation has shown that each type of limit state can be adequately represented; however it could require a high number of sampling points.
Consistently, enhancer classification based on their epigenetic state has shown that ~57% (2212) of H3K9me2-enriched enhancers in EpiLCs still retain significant H3K27ac, which we further confirmed using lcChIP-qPCR.
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