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Chinese electronic medical record named entity recognition method and system based on attention mechanism

A technology for named entity recognition and electronic medical records, which is applied in the fields of electrical digital data processing, instruments, biological neural network models, etc., to achieve the effect of improving performance

Pending Publication Date: 2020-03-06
山东健康医疗大数据有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0014] The technical task of the present invention is to provide a Chinese electronic medical record named entity recognition method and system based on the attention mechanism to solve the problem of how to recognize the named entity in the electronic medical record more accurately and conveniently based on the neural network and the attention mechanism

Method used

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  • Chinese electronic medical record named entity recognition method and system based on attention mechanism
  • Chinese electronic medical record named entity recognition method and system based on attention mechanism
  • Chinese electronic medical record named entity recognition method and system based on attention mechanism

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Embodiment 1

[0080] as attached figure 1 Shown, the Chinese electronic medical record named entity recognition method based on the attention mechanism of the present invention, the method steps are as follows:

[0081] S1. Based on the word vector modeling method, obtain the word vector and part-of-speech vector representation of the Chinese word part-of-speech and splicing the word vector and the part-of-speech vector; the specific steps are as follows:

[0082] S101, using the Skip-gram method of the word2vec model to generate a word vector w i ; Use the Skip-gram method of the word2vec model to generate word vectors. Skip-Gram is essentially a neural network model, and its basic structure includes an input layer, a hidden layer, and an output layer; the specific steps are as follows:

[0083] S10101. At the beginning of Skip-Gram, a One-Hot representation is input through the input layer, that is, the words in the sentence sequence are arranged in order, and the One-Hot corresponding t...

Embodiment 2

[0119] The Chinese electronic medical record named entity recognition system based on the attention mechanism of the present invention, the system includes,

[0120] The word vector and part-of-speech vector acquisition and splicing unit are used to obtain the word vector and part-of-speech vector representation of the Chinese word part-of-speech based on the word-vector modeling method and splicing the word vector and the part-of-speech vector;

[0121] The positive and negative hidden layer vector acquisition unit is used to input the Double-LSTMs neural network model for feature extraction based on word vector and part-of-speech vector splicing;

[0122] The attention layer construction unit is used to construct a layer of attention layer based on the Double-LSTMs neural network, which gives higher weight to relatively important information in the text and highlights its role;

[0123] The hidden layer vector splicing unit is used to assign weights to the corresponding hidd...

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Abstract

The invention discloses a Chinese electronic medical record named entity recognition method and system based on an attention mechanism, and belongs to the field of text information mining. The technical problem to be solved by the invention is how to identify named entities in an electronic medical record more accurately and conveniently based on a neural network and an attention mechanism. According to the technical scheme, the method comprises the following steps: S1, obtaining word vector and part-of-speech vector representation of Chinese word part-of-speech and splicing the word vector and the part-of-speech vector; S2, splicing the word vector and the part-of-speech vector, and inputting the spliced word vector and part-of-speech vector into a Double-LSTMs neural network model for feature extraction to obtain more accurate implicit strata vector representation; S3, adding an attention layer, and endowing relatively important information in the text with a higher weight; S4, endowing the weight with a hidden layer vector obtained by corresponding forward encoding and a hidden layer vector obtained by reverse encoding, and respectively splicing the hidden layer vectors to serveas feature vectors; and S5, carrying out sequence labeling based on the conditional random field model to realize an identification task of the named entity.

Description

technical field [0001] The invention relates to the technical field of text information mining, in particular to a Chinese electronic medical record named entity recognition method and system based on an attention mechanism. Background technique [0002] The continuous development of medical informatization has produced a large amount of medical data, especially the generation of electronic medical records. How to use natural language processing technology to process electronic medical records and extract important information from them to serve doctors' clinical decision-making has far-reaching research significance. , so named entity recognition technology is proposed. [0003] At present, the main methods applied to named entity recognition in Chinese electronic medical records can be roughly divided into three types: methods based on rules and dictionaries, methods based on statistical learning, and methods that combine the two methods. [0004] Among them, the method b...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/295G06F40/242G06N3/04G16H10/60
CPCG16H10/60G06N3/045
Inventor 谷兴龙王庚
Owner 山东健康医疗大数据有限公司
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