Intensive learning based medical natural language semantic network feedback extraction system and method

Abstract

The invention discloses an intensive learning based medical natural language semantic network feedback extraction system and method. The system comprises a medical text big-data module, a medical ontology extraction module, a medical semantic network module and a quality medical semantic network database module; the medical text big-data module comprises an electronic medical record, biomedical literature, biomedical patents and network forum data; the medical ontology extraction module is used for extracting a series of biomedical entities from a medical text; the medical semantic network module takes the medical entities as nodes and form the network by taking ontological relations as connections; the quality medical semantic network database module forms high-quality structured data through the medical semantic network via crowdsourcing proofreading and experts proofreading and is used for intensive learning and training of the relationship extraction neural network.

Description

technical field [0001] The invention relates to the field of medical big data, in particular to a system and method for feedback extraction of medical natural language semantic network based on reinforcement learning. Background technique [0002] In the process of disease discovery and treatment, doctors make corresponding diagnoses according to the different characteristics of patients. Therefore, discovering the relationship between patient characteristics and treatment methods can guide doctors to choose appropriate drugs and treatment methods. Existing correlation analysis methods usually conduct simple hypothesis testing on patient information and treatment methods in turn, and the data sources are usually limited to structured standard databases, the amount of data collection and processing is small, and there is a lack of automated implementation methods. Therefore, since a large amount of disease-related data exists in the form of unstructured natural language, a s...

AI Technical Summary

Problems solved by technology

Existing correlation analysis methods usually conduct simple hypothesis testing on patient information and treatment methods in turn, and the data sources are usually limited to structured standard databases, the amount of data collection and processing is small, and there is a lack of automated implementation methods

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