This invention discloses an
autism-assisted diagnostic method and
system based on
gene pathway mapping information, belonging to the interdisciplinary field of
bioinformatics and
machine learning. The invention first reads and preprocesses raw
sequencing data to obtain a standardized differentially expressed
gene matrix; then, it introduces pathway function and
topological information to construct a pathway topological
adjacency matrix, and obtains
gene pathway features by
dimensionality reduction, graph
signal propagation, and feature encoding of the pathway
feature matrix; subsequently, it performs initial training of a multimodal fusion
network on the aforementioned two matrices; then, it selects Top K
key genes based on gene importance scores and performs secondary training in conjunction with
gene pathway features; finally, it inputs the
gene expression levels of the subject to be tested and outputs the
autism-assisted diagnostic classification results. By introducing
gene pathway mapping as prior knowledge, this invention constructs a multimodal fusion network that combines biological
interpretability and high robustness, which can improve the accuracy of
autism diagnosis based on a small number of key features.