The invention belongs to the technical field of medical
image analysis, and particularly discloses a method and
system for predicting the electroshock
treatment effect of a teenager patient with severe depression, and the method comprises the steps: collecting the structural
magnetic resonance imaging data of the teenager patient with depressive disorder before and after electroshock treatment ECT, and carrying out the preprocessing; obtaining brain
grey matter morphological characteristics of the teenager depressive disorder patient; the method comprises the following steps: constructing a brain structure connection network of a patient based on brain
grey matter morphological characteristics of a teenager depressive disorder patient; based on a brain structure connection network and a
graph theory, extracting topological features of a
brain network; and inputting the extracted
brain network topology features into a two-stage
machine learning model for
curative effect prediction. According to the technical scheme, the most representative key information is extracted, and the brain structure network features and the
machine learning technology can be effectively fused, so that the prediction accuracy of the ECT
curative effect of the teenager MDD patient is improved.