Triage method and device based on neural network model and computer equipment
A neural network model and model technology, applied in biological neural network models, neural learning methods, computer-aided medical procedures, etc., can solve the problem of low accuracy of triage products, and achieve improved recognition accuracy, simple input, The effect of improving usability
Pending Publication Date: 2020-10-16
PING AN TECH (SHENZHEN) CO LTD
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[0003] The main purpose of this application is to provide a triage method, device and computer equipment based on the neural network model, aiming to solve the problem of low triage accuracy of triage products
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[0048] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0049] refer to figure 1 , the embodiment of the present application provides a kind of 1, a kind of triage method based on neural network model, comprises the following steps:
[0050] S1. Receive the disease information input by the person to be triaged;
[0051] S2. Using the pre-training model BERT to semantically encode the disease information to obtain disease codes, wherein the pre-training model BERT vectorizes each character in the disease information to obtain a character vector for each character, and Mark the position vector for each character to obtain the c...
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The invention relates to artificial intelligence, and provides a triage method and device based on a neural network model and computer equipment. The method comprises the following steps: receiving disease information input by a patient to be triage; performing semantic coding on the disease information by using a pre-training model BERT to obtain a disease code; inputting the disease code into apreset BiLSTM + CRF sequence labeling model for calculation to obtain a standard symptom corresponding to disease information; and obtaining triage information according to the standard symptoms, feeding back the triage information to the to-be-triage person, and performing semantic recognition by using a pre-training model BERT when the to-be-triage person executes the method, thereby improving the recognition accuracy of the standard symptoms, and improving the understanding of spoken input symptom information at the same time. The pre-training model BERT and the BiLSTM + CRF sequence labeling model can be stored in a block chain network. The invention further provides a human body medical knowledge graph which is used by the elderly or children and other people who cannot describe the illness state, the trouble of character input is avoided to a certain extent, and the availability is improved.
Description
technical field [0001] This application relates to the field of artificial intelligence, in particular to a neural network model-based triage method, device and computer equipment. Background technique [0002] Triage products refer to artificial intelligence products that automatically perform triage based on disease information to remind users which department number they should register for medical treatment. Existing products mainly rely on rules for symptom recognition and lack flexibility. Triage products are aimed at ordinary users, and the input is mainly colloquial symptoms, which are difficult to directly map to standard symptoms, and the accuracy of triage is poor. Contents of the invention [0003] The main purpose of this application is to provide a triage method, device and computer equipment based on a neural network model, aiming at solving the problem of low triage accuracy of triage products. [0004] In order to achieve the above-mentioned purpose of t...
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IPC IPC(8): G16H50/20G06F40/35G06F40/279G06N3/04G06N3/08
CPCG16H50/20G06F40/279G06F40/35G06N3/049G06N3/08G06N3/045
Inventor 林桂黎旭东
Owner PING AN TECH (SHENZHEN) CO LTD