The invention provides a Chinese herbal
medicine composition
blood vessel protection effect prediction method and
system based on
deep learning. The method comprises the following steps: firstly, acquiring
spectral data of Chinese herbal medicines, and separating characteristic signals of
active components through an optical filtering unit; a principal component dimension reduction module and a molecular polarity sensing layer of a deep neural network are utilized to analyze phase offsets of different polarity components, feature weights are dynamically adjusted, a correlation model of spectrum parameters and
active component concentrations is established, and a component characteristic spectrum is generated. And then, dynamically distributing the
wave band weight of the characteristic spectrum through a multi-channel attention module, comparing the
wave band weight with a target activity threshold interval in a vascular
cell response
database, and optimizing the characteristic spectrum. And finally, inputting the optimized characteristic spectrum into a neural
network model, and outputting a quantized value of the
blood vessel protection effect after matching characteristic dimensions. The spectral characteristics of the Chinese herbal medicines are dynamically analyzed through
deep learning, and the
blood vessel protection effect is accurately quantified.