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We classify the use of patient strategies as a societal-level determinant of healthcare utilization with the understanding that the use of patient strategies functions as a norm of social interaction that indicates the development of tacit knowledge guiding interpersonal interactions in the healthcare setting.
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Therefore, we classify the results using neural networks.
We classified the households using quintiles as cut-off points.
The analysis by region used postcode classified using the Australian Standard Geographical Classification Remoteness Area.
Sequences were classified using the RDP classifier program implemented in mothur using the bayesian method.
The data are classified using the therapeutic groups of the British National Formulary.
The hits were classified using the ranking product method (Breitling et al., 2004) using the triplicates.
For the latter, the CNPs are classified using the Bayesian classification rule.
Subsequently, the remaining low-confidence points are classified using the trained classifier.
The shapes of the lingula were classified using the classification proposed by Tsai [ 4].
The outcomes measured in the trials were classified using the International Classification of Functioning, Disability and Health ICFF).
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