A 2013 survey conducted by Pew Research Center found that social media was enhancing the arts based on a boost of performances, greater audience participation, and wider access to grants, particularly ones from the NEA.
Variant prioritization is based on a proposed boosting method, which not only outperforms two other methods (SNPiR and VQSR) in overall performance, but also provides great flexibility to users for adjusting of the precision/recall trade-off, and it is superior to ad hoc hard-threshold approaches, such as SNPiR.
Patients typically started a first suppression episode with cART based on either a boosted protease inhibitor (PI, 47 %) or a non-nucleoside reverse transcriptase inhibitor (NNRTI, 42 %), but the latter was less common in subsequent episodes (30%%).
Our method is based on a semi-supervised boosting framework that samples some useful unlabeled data at each iteration to improve the performance of the underlying classifier (SVM in this paper).
The proposed STATCOM is based on a hybrid Boost Modular Multilevel Converter (hybrid BMMC) with a reduced number of Full-Bridge SubModules (FB-SMs).
The researchers devised a machine-learning algorithm that is based on a gradient-boosting regression methodology, in which thousands of decision trees were derived to optimize the predictive value of the overall model.
One of the most advanced approaches is based on a prime-boost immunization using two different viral vectors (vaccinia virus and fowlpox, respectively) expressing a prostate cancer antigen (PSA) and three different co-stimulatory molecules (B7-1, LFA-3, and ICAM1).
Here, we propose an approach for choosing summary statistics based on boosting, a technique from the machine-learning literature.
It is based on boosting, a method developed in machine learning to establish the relationship between predictors and response variables in complex models (Schapire 1990; Freund 1995; Freund and Schapire 1996, 1999).
Based on the boosting technique, a group additive regression model [ 27] and a nonparametric pathway-based regression model [ 28] were developed to identify groups of genomic features that are related to several clinical phenotypes, including the survival outcome.
