Medical record structured analysis method based on medical field entities

A structured and physical technology, applied in unstructured text data retrieval, special data processing applications, instruments, etc., to improve accuracy, avoid ambiguity, and improve recognition results

Active Publication Date: 2019-07-19
微医云(杭州)控股有限公司
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  • Application Information

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Problems solved by technology

[0015] The purpose of the present invention is to provide a method for structured analysis of medical records base

Method used

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  • Medical record structured analysis method based on medical field entities
  • Medical record structured analysis method based on medical field entities
  • Medical record structured analysis method based on medical field entities

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[0028] The present invention will be further described in detail below with reference to the drawings and embodiments.

[0029] figure 1 It is a framework diagram of the overall implementation of a medical record structured analysis method based on entities in the medical field in this application. The method includes the following steps:

[0030] The first step: Medical researchers select entities in the medical field. The entities in the medical field mainly include: diseases, symptoms, drugs, examinations, signs, and treatments. Table 1 is a framework corresponding to the attributes of the medical records defined in this application;

[0031] Table 1:

[0032]

[0033] Step 2: Build a mapping relationship table between entities and attributes; the attributes are also set by practitioners with medical experience in combination with business needs, including: location, occurrence time, duration, frequency, size, quantity, degree, incentives , Aggravating factors, mitigating factors,...

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Abstract

The invention discloses a medical record structured analysis method based on medical field entities, and the method comprises the steps of 1) building a medical entity and an attribute category tablefor a common medical record text, and carrying out the corresponding relation mapping; 2) identifying the medical entity in the medical record text by adopting a Bert _ BiLSTM _ CRF model; 3) segmenting the medical record text according to semantics to form events; 4) recombining the events; 5) constructing an attribute recognition model, and extracting the attributes in the segmented events; 6) connecting the medical entities of the events in the same sentence by utilizing the knowledge graph to obtain the relationship between the entities, and 7) customizing different attribute recognition models for different types of medical record text segments, and finally forming a final medical record structured analysis text according to the text sequence accumulating structured analysis results.

Description

technical field [0001] This application relates to a method for structured analysis of medical records based on entities in the medical field. Background technique [0002] Entities in the medical field have their particularities, mainly including symptoms, diseases, drugs, treatments, signs, inspections, and so on. [0003] Text structuring mainly uses algorithms to extract information relations, and converts unstructured or semi-structured text data into a format that can be automatically analyzed and processed by computers. [0004] In medical record structuring, due to the specificity of medical record text writing, it is difficult to obtain better structured results by using traditional information relationship extraction methods or syntactic analysis models. A common method of structuring medical record texts is to identify medical entities in medical records and perform relationship mapping on medical entities. Due to the complexity of entities and their relationship...

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Application Information

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IPC IPC(8): G06F16/36G06F17/27G16H10/60
CPCG06F16/367G16H10/60G06F40/30
Inventor 毛葛永孟海忠吴边尹伟东任宇翔陈啸冬曹晓光
Owner 微医云(杭州)控股有限公司
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