The application provides an anatomic structure segmentation-based medical
age and gender prediction framework and an explanation
system, comprising: a data preprocessing and
standardization module for cleaning, enhancing and normalizing input medical images; an
age and gender feature extraction and prediction module for constructing and training a
deep learning model to extract features from the medical images processed by the data preprocessing and
standardization module and predict age or gender labels; a model explanation extraction module under structural constraints for taking medical prior segmentation results as structural constraints, generating model decision explanations aligned with medical structures based on intermediate layer feature maps and prediction outputs obtained by the
age and gender feature extraction and prediction module through a dual-view technology path; and an explanation reliability
verification module for quantitatively verifying the causal fidelity and rationality of the explanation results of the model explanation extraction module under structural constraints through a gradual intervention strategy, so as to improve the quality and
readability of the explanation.