ADHD pathogenic subcutaneous nucleus prediction method, system and device and storage medium

Abstract

The invention discloses an ADHD pathogenic subcutaneous nucleus prediction method, system and device and a storage medium. The method comprises the following steps: acquiring a first magnetic resonance image data set of each subtype ADHD case, a second magnetic resonance image data set of a normal child subcutaneous nucleus and first scale data of each subtype case; carrying out subcutaneous nucleus structure covariant analysis on the first magnetic resonance image data set and the second magnetic resonance image data set to obtain a first abnormal subcutaneous nucleus; obtaining a first contribution score according to the two subcutaneous brain area volumes of the first abnormal subcutaneous nuclei; obtaining a trained prediction regression model according to the first contribution score and the first scale data; and inputting a first magnetic resonance image of an ADHD case to be predicted into the prediction regression model to obtain a prediction result of the subcutaneous nuclei. The method can provide effective scientific basis for clinical treatment and rehabilitation decision. The method can be widely applied to the technical field of medicine.

Description

technical field [0001] The present application relates to the field of medical technology, in particular to a method, system, device and storage medium for predicting ADHD pathogenic subcutaneous nuclei. Background technique [0002] Attention deficit hyperactivity disorder (ADHD, ADHD for short) is a common neuropsychiatric disorder. The incidence of ADHD is about 5-7% in children and about 2.5% in adults, and has been increasing in recent years. ADHD is clinically divided into three subtypes: the first is a rare subtype dominated by hyperactivity-impulsivity (ADHD-Hyperactive); the second is a more common subtype dominated by attention deficit (ADHD- Inattentive); the third is the most common hyperactivity and attention deficit mixed subtype (ADHD-Combined). Growing evidence suggests that the attention deficit subtype of ADHD is a disorder distinct from the other two subtypes, with distinct cognitive and behavioral characteristics and underlying neurobiological underpinn...

AI Technical Summary

Problems solved by technology

In the prior art, most ADHD symptom assessments use EEG, eye movement, behavioral scales, etc. to evaluate the cognitive level and symptoms of ADHD children, but there is not enough attention and research on abnormal subcutaneous nuclei, and there is no targeted A method for predicting pathogenic subcutaneous nuclei from brain imaging data of patients. Therefore, a new method for predicting pathogenic subcutaneous nuclei in ADHD is urgently needed

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