Machine Learning Technologies and Psychological Testing of Pre-School and Primary School-Aged Children in Diagnostics of Perinatal Affection of the Central Nervous System
The present study deals with computer-assisted learning technologies used for the analysis of psychological test results of children to diagnosis perinatal affection of the central nervous system. The mathematical models of logistic regression and gradient boosting give the best results within the accuracy of 81%.
Keywords: Machine learning, children, central nervous system, perinatal affection.
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