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Medical text named entity recognition method and device

A named entity recognition and text technology, applied in the field of medical text named entity recognition, can solve problems such as inability to adapt to language phenomena, inability to consider medical text context information, etc., and achieve the effects of high speed, high recognition accuracy, and high recall rate.

Active Publication Date: 2018-09-21
北京颐圣智能科技有限公司
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Problems solved by technology

However, pure dictionary-based methods can neither consider contextual information in medical texts nor adapt to complex linguistic phenomena and output globally optimal results

Method used

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  • Medical text named entity recognition method and device
  • Medical text named entity recognition method and device
  • Medical text named entity recognition method and device

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Embodiment Construction

[0047] According to the following detailed description of specific embodiments of the application in conjunction with the accompanying drawings, those skilled in the art will be more aware of the above and other objectives, advantages and features of the application.

[0048] see figure 1 According to one aspect of the present invention, a method for named entity recognition of medical text is provided, comprising:

[0049] Step S11: Input the medical text into the forward long-term short-term memory network and the backward long-term short-term memory network respectively, and obtain the first output result and the second output result;

[0050]Step S12: using the first activation function to map the first output result and the second output result respectively, and combine the mapped results to obtain a third output result;

[0051] Step S13: Use the second activation function to calculate the third output result to obtain an n*r-dimensional matrix P, where n represents the...

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Abstract

The invention discloses a medical text named entity recognition method and device. The method comprises the following steps of: respectively inputting a medical text into a forward long and short-termmemory network and a backward long and short-term memory network so as to obtain a first output result and a second output result; respectively mapping the first output result and the second output result by utilizing a first activation function, and combining the mapped results to obtain a third output result; calculating the third output result by utilizing a second activation function so as toobtain an n*r-dimensional matrix P; and substituting the matrix P into a conditional random field transfer matrix, and calculating and obtaining a global optimum label sequence corresponding to a named entity. According to the method, the medical term recognition correctness and recall rate are high, the calculation speed is high, and medical term recognition can be rapidly carried out, so that model calculation and prediction can be carried out.

Description

technical field [0001] The present application relates to the medical and health field, and in particular relates to a medical text named entity recognition method and device, a computer device, a computer-readable storage medium and a computer program product. Background technique [0002] In 1968, in order to make it easier for medical staff to diagnose and reason patients' conditions, Dr. Weed proposed to organize electronic medical records oriented to problems. Since then, clinical decision support research based on medical texts such as electronic medical records has attracted much attention. This research usually requires the application of natural language processing, information extraction and other technologies to process medical texts to identify entities and entity relationships in the text; then, based on these Data to train medical models, and use medical models to predict and analyze human health. Therefore, the accuracy of entity and entity relationship recog...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06N3/04G06N3/08
CPCG06N3/08G06F40/289G06F40/295G06N3/044G06N3/045
Inventor 不公告发明人
Owner 北京颐圣智能科技有限公司
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