The invention discloses a
diagnostic reasoning RAG
system for resisting retrieval
noise based on a self-generated
knowledge base, and the
system comprises a
knowledge retrieval module which carries out the retrieval from an external
knowledge base according to a user question to obtain a plurality of
target text blocks; the evaluation generation module is used for independently evaluating each
target text block through an evaluation model so as to identify retrieval
noise, generating a correlation judgment result and a
noise degree judgment result of each
target text block, and generating
internal memory information as a self-generated
knowledge base based on a user question; and the diagnosis reasoning module is used for integrating the user question, each target text block, the corresponding correlation judgment result, the noise degree judgment result and the
internal memory information into enhanced prompt information and inputting the enhanced prompt information into a large
language model to generate a diagnosis reasoning answer. According to the method, retrieval noise interference can be effectively resisted, model knowledge support is strengthened by means of the self-generated knowledge base, the precision and timeliness of
medical diagnosis reasoning are improved, and the requirements of the medical field for high-precision and strong-timeliness
clinical decision making are met.