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Are males more likely to be addicted to the internet than females? A meta-analysis involving 34 global jurisdictions.
Wenliang Su
Xiaoli Han
Cheng Jin
Yan Yan
Marc N. Potenza
Published in:
Comput. Hum. Behav. (2019)
Keyphrases
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meta analysis
microarray data
gender differences
statistically significant
males and females
data sets
gene expression profiles
real world
data mining
machine learning
object recognition
support vector machine
significantly higher