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

A semantic network and reinforcement learning technology, applied in the field of medical big data, can solve the problems of small amount of data collection and processing, lack of automatic implementation methods, etc.

Inactive Publication Date: 2018-06-29
苏州迪美格智能科技有限公司
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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

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

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[0015] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0016] figure 1 It is a block diagram of the reinforcement learning-based medical natural language semantic network feedback extraction system and method of the present invention.

[0017] like figure 1 As shown, the present invention is based on reinforcement learning medical natural language semantic network feedback extraction system and method, including medical text big data module, medical ontology extraction module, medical semantic network module, quality medical semantic network database module; The text big data module includes electronic medical records, biomedical literature, biomedical patents and network forum data; the medical ontology extraction module is used to extract a series of biomedical ontol...

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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...

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Application Information

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IPC IPC(8): G06F17/27G06F17/30G06N3/08G16H50/70
CPCG06N3/08G06F16/3335G06F16/367G06F40/279G06F40/30
Inventor 任思远
Owner 苏州迪美格智能科技有限公司
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