Pre-hospital emergency case text recognition method and device, terminal and storage medium
A recognition method and text technology, applied in neural learning methods, character and pattern recognition, unstructured text data retrieval, etc., can solve the problems of low accuracy rate of text classification of pre-hospital emergency cases, difficulty in identifying similar professional words, etc. To achieve the effect of improving accuracy and expressing comprehensive accuracy
Pending Publication Date: 2022-05-03
HEBEI UNIV OF ENG
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[0004] Embodiments of the present invention provide a method, device, terminal and storage medium for identifying texts of pre-hospital emergency cases, so as to solve the problem in the prior art that it is difficult to identify similar professional vocabulary, which leads to a decrease in the classification accuracy of pre-hospital emergency case texts
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[0048] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
[0049] In order to make the purpose, technical solution and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.
[0050] figure 1 The implementation flowchart of a pre-hospital emergency case text recognition method provided by the embodiment of the present invention is described in detail as follows:
[0051] S...
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The invention provides a pre-hospital emergency case text recognition method and device, a terminal and a storage medium. The method comprises the following steps: preprocessing an obtained pre-hospital emergency case text to obtain a processed target text; dynamically coding each word according to the context of the target text to obtain a word vector; performing global information extraction and local information extraction on the word vector, and performing information fusion on the extracted global information and local information to obtain a feature vector; and inputting the feature vector into a target image convolutional neural network model for text classification and recognition. According to the method, accurate extraction of similar professional vocabularies can be realized, so that the accuracy of text classification and recognition can be improved, and the extraction of global features and local features of word vectors is realized, so that the extracted feature vectors are expressed more comprehensively and accurately.
Description
technical field [0001] The present invention relates to the technical field of text data processing, in particular to a text recognition method, device, terminal and storage medium for pre-hospital first aid cases. Background technique [0002] Pre-hospital first aid plays an important role in the medical treatment of saving lives and helping the wounded. The pre-hospital first aid system mainly relies on the experience and work efficiency of the operators. When the operator receives the emergency call, he should understand the cause of the patient's disease, basic situation and living conditions in a short time, and record the condition information of the emergency patient in the pre-hospital emergency case text. Deep learning has been applied in information extraction and static prediction in electronic medical records, and has achieved good results. Therefore, the text classification model based on deep learning can be used to extract the semantic features in the text of ...
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IPC IPC(8): G06F16/35G06K9/62G06N3/04G06N3/08G16H10/60
CPCG06F16/35G16H10/60G06N3/08G06N3/045G06F18/214G06F18/2411
Inventor 生龙张旭田丰赵继军陈湘国马晓雨魏忠诚王巍王超
Owner HEBEI UNIV OF ENG