This invention relates to a method and system for intelligent editing of medical forms. The method includes: performing version number verification in response to user-input natural language editing instructions; after successful verification, reading the corresponding original form abstract syntax tree from a medical database and inputting the natural language editing instructions and the summary information of the original form abstract syntax tree into a directed graph editing pipeline; outputting an operation instruction list or clarification request through an operation planning node, and performing multi-level verification on the operation instruction list through an operation verification node when outputting the operation instruction list; and feeding back the clarification question to the front end for visualization through a clarification return node when outputting the clarification request. After the multi-level verification is successful, executing the operation instruction list through an operation execution node to generate the target form abstract syntax tree; performing structural verification on the target form abstract syntax tree, and writing the target form abstract syntax tree into a data table after successful structural verification to obtain the target medical form.
This invention relates to the field of drug safety assessment technology, and particularly to a drug safety assessment method and system based on multi-source data fusion. The method includes: receiving the SMILES structural formulas and research information of candidate drugs; encoding the SMILES structural formulas of the candidate drugs and each combination drug to obtain molecular structure feature vectors; constructing a knowledge graph by fusing multiple public biomedical databases to obtain knowledge graph embedding vectors; performing cross-modal multi-source information fusion on the molecular structure feature vectors and knowledge graph embedding vectors to obtain a multi-source fusion representation vector; inputting the concatenated vector into a prediction model to predict and calibrate drug-drug interactions and adverse reactions, obtaining calibration confidence levels; and conducting a safety assessment of drug interactions based on indications and calibration confidence levels, generating a comprehensive safety assessment report. This invention provides a reliable reference for decision-making regarding the safety of combination drug use during the drug development stage.
A brain-like auxiliary diagnosis and treatment method for rare diseases is realized based on a GPU or NPU server, a system review agent is used as a sensing front end of the method, is connected with an external medical database through a standard API interface, executes automatic retrieval and quality preliminary screening of literatures, and outputs an original literature set; the document processing agent is used for receiving an original document set of the system review agent, performing structured extraction on an unstructured PDF document by utilizing a deep analysis tool, and generating a structured knowledge base containing a core clinical field; and the NHSC brain-like agent adopts a brain-like architecture based on a dual processing theory, receives the structured knowledge base and the patient data of the document processing agent, and outputs a final dynamic diagnosis and treatment suggestion through fast and slow dual-channel cooperative processing. Algorithm evaluation of evidence quality is realized, an evidence screening mechanism is enhanced from the source, risks caused by illusion of a large language model are effectively reduced, and stability and reliability of an evidence synthesis result are guaranteed.