In sum, these dimensions are categorized into three classifications: "Personal factors" (i.e., degree of fit with life style and passion in life), "social influences" (i.e., reference group acceptance, collective memory, and social visibility), and "VCE identification and engagement" (i.e., VCE identification and VCE engagement).
For the purposes of this study the pathologies were categorized into 15 classifications.
Coronary artery stenosis was categorized into three classifications: normal (any coronary artery stenosis <25%), mild to moderate (any coronary artery stenosis ≥25%), and severe (three coronary artery stenosis ≥50%; coronary artery bypass surgery).
Transcripts encoding proteins of known functions were manually categorized into the functional classification described by Bevan et al. [ 54], with reference to the scarlet runner bean (SRB) embryonic EST project (http://www.mcdb.ucla.edu/Research/ Goldberg).
Proposed approaches are generally categorized into two main classifications: the first category detects and modifies outliers in the pre-processing stage adaptively and then prepares the modified data for processing.
All 47 groups can be categorized into three main classifications: "cellular component", "molecular function" and "biological process".
Depression was categorized into a binomial severity classification that differentiated between no or mild depression (PHQ-9 scores <10) and moderate to severe depression (PHQ-9 scores ≥10).
PHQ-9 scores were categorized into a binomial depression severity classification using standardized cutoffs that differentiated between no or mild depression (PHQ-9 scores <10) and moderate to severe depression (PHQ-9 scores ≥10) (Kroenke et al. [2001]).
After clinical evaluation, electrocardiography and laboratory examination participants were categorized into a stratified six-level classification system according to their health status, going from A (completely healthy) to D (signs of active disease at the moment of examination).
Samples can be categorized into four groups after a classification process, which is denoted in the confusion matrix presented in Table 2. Since the sample in the positive class has the high identification importance, we only evaluate our approach based on the performance of the positive class.
