Child attention deficit hyperactivity disorder judgment method based on social network analysis

Abstract

A child attention deficit hyperactivity disorder judgment method based on social network analysis includes the following steps that first, nuclear magnetic data are preprocessed, wherein first, the data are normalized and processed in a unified mode, standard brain space is used for measuring different shapes of brains of experimenters in space normalization, and the different shapes of brains of the experimenters can be described with one coordinate system; then, the preprocessed fMRI data are partitioned according to standards to form sub-partitions for subsequent processing and analysis; second, characteristic sets of all attributes based on a brain network are calculated and shown in the forms of graphs and line charts. The method is combined with social network attribute characteristics, more appropriate attribute characteristics are provided for deep analysis of specific areas, advantages of social network analysis relative to existing network analysis and research are better given play to, the typical meaning of the attribute characteristics is presented prominently through difference between ADHD and control groups, meanwhile, the expression of ADHD different from that of the control groups in the specific areas is found, and therefore pathological changes and development of the ADHD can be analyzed and researched through the specific expression in the specific areas.

Description

technical field [0001] The invention relates to a method for judging ADHD in children based on social network analysis in the field of artificial intelligence and intelligent computing. technical background [0002] ●ADHD NMR data [0003] ADHD (Attention Deficit Hyperactivity Disorder) is a behavioral disease that often occurs in school-age children. It is specifically manifested as inattention, hyperactivity, etc., such as difficulty in concentrating on something or It is difficult to control their behavior, often barking, etc. These phenomena will last for a long time on the patient and may have a great impact on his life and psychology. [0004] Based on ADHD fMRI (functional magnetic resonance imaging, functional magnetic resonance imaging) data, that is, brain tomographic image data obtained by using functional magnetic resonance imaging for ADHD patients, can accurately reflect the activities of various functional regions of the brain. Blood oxygen level-dependent ...

AI Technical Summary

Problems solved by technology

Specifically, for this purpose, the present invention provides a method for judging children's ADHD based on social network analysis, which utilizes the advantages of multiple attribute characteristics of the social network analysis method, and can accurately quantify social network attributes, with detailed attribute feature values, charts and other forms to quantify the abnormal brain regions of ADHD patients, so as to achieve the purpose of distinguishing ADHD in children and overcome the shortcomings of existing research methods that are not accurate

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