This invention discloses a method and
system for constructing an AI-assisted
diagnostic agent for
pulmonary embolism based on ontology and
knowledge graph, belonging to the fields of
medical information systems and medical
artificial intelligence technology. By integrating a
pulmonary embolism-specific medical ontology, a clinically aligned
knowledge graph, and thought chain reasoning, this invention leverages the hard constraints of ontology knowledge to achieve
interpretability analysis of the entire process of AI-assisted diagnosis for
pulmonary embolism, precise suppression of AI illusions specific to pulmonary
embolism, end-to-end
quality control, and closed-
loop optimization. It is particularly suitable for rapid diagnosis of acute and critical pulmonary
embolism, AI-assisted identification of
pulmonary artery filling defects in CTPA images,
thrombosis severity stratification, and
emergency treatment decision tracing and regulatory compliance
quality control scenarios. It can be adapted to the implementation, regulatory
verification, and clinical optimization of various pulmonary
embolism AI
imaging diagnostic and emergency auxiliary diagnosis and treatment systems, specifically addressing core illusion problems in pulmonary embolism AI diagnosis such as false positive
embolus identification and disordered
risk stratification.