Disease prediction method and device, computer device and readable storage medium

A prediction method and disease monitoring technology, applied in computer-aided medical procedures, epidemic warning systems, medical automated diagnosis, etc., can solve problems such as insufficient effects and affecting the accuracy of disease prediction, and achieve improved accuracy and high accuracy , the effect of improving the prediction accuracy

Inactive Publication Date: 2018-10-12
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, traditional machine learning applied to disease prediction often needs to manually define a feature set, and then search for the bes

Method used

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  • Disease prediction method and device, computer device and readable storage medium
  • Disease prediction method and device, computer device and readable storage medium
  • Disease prediction method and device, computer device and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] figure 1 It is a flow chart of the disease prediction method provided in Embodiment 1 of the present invention. The disease prediction method is applied to a computer device. The disease prediction method utilizes the long-short-term memory recurrent neural network model to predict the disease monitoring data, and obtains a high-accuracy disease prediction result.

[0055] like figure 1 As shown, the disease prediction method specifically includes the following steps:

[0056] Step 101, acquiring disease monitoring data, where the disease monitoring data is time series data.

[0057] The disease monitoring data may include prevalence data of diseases such as influenza, hand, foot and mouth disease, measles, and mumps.

[0058] A disease monitoring network composed of multiple monitoring points can be established in a preset area (such as provinces, cities, and regions), and disease monitoring data can be obtained from the monitoring points, and the time series data ...

Embodiment 2

[0115] figure 2 It is the weather data related to the disease monitoring data obtained in the disease prediction method provided in Embodiment 2 of the present invention (ie figure 1 The detailed flowchart of step 102).

[0116] The weather data can be captured through a web crawler by using an API interface opened by a weather information website. refer to figure 2 As shown, specifically, the following steps may be included:

[0117] Step 201, generating a seed URL and subsequent URLs facing the API interface of the weather information website.

[0118] The seed URL is the basis and premise for all work performed by web crawlers. There can be one or more seed URLs.

[0119] The structural characteristics of the URL of the weather information website can be analyzed, and subsequent URLs can be obtained according to the structural characteristics of the URL.

[0120] Step 202, sending an HTTP request to the API interface of the weather information website, requesting to a...

Embodiment 3

[0132] image 3 A structural diagram of a disease prediction device provided in Embodiment 3 of the present invention. like image 3 As shown, the disease prediction device 10 may include: a first acquisition unit 301 , a second acquisition unit 302 , a third acquisition unit 303 , a preprocessing unit 304 , a construction unit 305 , an optimization unit 306 , and a prediction unit 307 .

[0133] The first acquiring unit 301 is configured to acquire disease monitoring data, where the disease monitoring data is time series data.

[0134] The disease monitoring data may include prevalence data of diseases such as influenza, hand, foot and mouth disease, measles, and mumps.

[0135] A disease monitoring network composed of multiple monitoring points can be established in a preset area (such as provinces, cities, and regions), and disease monitoring data can be obtained from the monitoring points, and the disease monitoring data can form time series data for disease monitoring. ...

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Abstract

The invention provides a disease prediction method. The method comprises the steps that the disease monitoring data, the weather data and the public opinion data are acquired; the disease monitoring data, the weather data and the public opinion data are preprocessed; a multilayer LSTM model is constructed; training and performance verification are performed on the multilayer LSTM model so as to obtain the optimized multilayer LSTM model; and the prediction time point is predicted by using the optimized multilayer LSTM model so as to obtain the disease prediction result of the prediction time point. The invention also provides a disease prediction device, a computer device and a readable storage medium. High-accuracy disease prediction can be realized.

Description

technical field [0001] The present invention relates to the technical field of prediction, in particular to a disease prediction method and device, a computer device and a computer-readable storage medium. Background technique [0002] With the acceleration of the process of global economic integration, the increase of economic and communication activities, the increasingly frequent flow of people provides a favorable environment for the spread and outbreak of diseases, and public health problems are becoming more and more serious. At the same time, social and natural environments are also changing, and the increase in environmental pollution, natural disasters and other incidents that affect public health also increases the possibility of outbreaks of public health emergencies. [0003] How to identify public health emergencies in an early stage, issue early warnings, and take corresponding control measures as soon as possible to minimize the losses caused by public health ...

Claims

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Application Information

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IPC IPC(8): G16H50/80
CPCG16H50/80G16H50/20G16H50/70
Inventor 阮晓雯徐亮肖京
Owner PING AN TECH (SHENZHEN) CO LTD
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