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Disease abnormality data detecting method, computer device and storage medium

A technology for abnormal data detection and disease monitoring, applied in the field of data processing, can solve problems such as low reference value, unsatisfactory, and prone to deviation in results, and achieve efficient and accurate abnormal detection, high applicability, and reasonable detection results.

Inactive Publication Date: 2018-09-28
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Existing anomaly detection methods, such as zscore anomaly detection method and Grubbs (Grubbs) anomaly detection method, require the data to meet the normal distribution, but in fact, this requirement cannot be met in many cases
For the traditional quartile method, all the data will be used, and the reference value of the long-term data to the current data is low, and the results are more likely to be biased

Method used

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  • Disease abnormality data detecting method, computer device and storage medium
  • Disease abnormality data detecting method, computer device and storage medium
  • Disease abnormality data detecting method, computer device and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0047] figure 1 It is a flow chart of the method for detecting abnormal disease data provided by Embodiment 1 of the present invention. The method for detecting abnormal disease data is applied to a computer device. The method for detecting abnormal disease data detects abnormal values ​​in the disease monitoring data, so that public health emergencies such as epidemics or outbreaks of diseases can be identified early, corresponding control measures are taken as early as possible, and losses caused by public health emergencies are reduced to lowest.

[0048] Such as figure 1 As shown, the abnormal disease data detection method specifically includes the following steps:

[0049] Step 101, acquire disease surveillance data from time point 0 to time point t to form time series data X, where X=[x 0 ,x 1 ,x 2 ,...,x t ].

[0050] The disease monitoring data may include monitoring data of influenza, hand, foot and mouth disease, measles, mumps and other diseases.

[0051] A...

Embodiment 2

[0094] figure 2 It is a structural diagram of a device for detecting abnormal disease data provided by Embodiment 2 of the present invention. Such as figure 2 As shown, the abnormal disease data detection device 10 may include: an acquisition unit 201, a calculation unit 202, a determination unit 203, and a judgment unit 204.

[0095] Acquisition unit 201, configured to acquire disease surveillance data from time point 0 to time point t to form time series data X, where X=[x 0 ,x 1 ,x 2 ,...,x t ].

[0096] The disease monitoring data may include monitoring data of influenza, hand, foot and mouth disease, measles, mumps and other diseases.

[0097] A disease monitoring network composed of multiple monitoring points can be established in a preset area (such as provinces, cities, and regions), and the disease monitoring data can be obtained from the monitoring points, and the time series data constituting the disease monitoring can be formed from the disease monitoring ...

Embodiment 3

[0140] This embodiment provides a computer-readable storage medium, and a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps in the above-mentioned embodiment of the method for detecting abnormal disease data are implemented, for example figure 1 Steps 101-105 shown:

[0141] Step 101, acquire disease surveillance data from time point 0 to time point t to form time series data X, where X=[x 0 ,x 1 ,x 2 ,...,x t ];

[0142] Step 102, select the time window size w, and for each time point i from time point w to time point t, calculate the mean value μ of the disease surveillance data in the time window corresponding to the time point i i and standard deviation σ i , the size of the time window corresponding to the time point i is w, i=w, w+1,...,t;

[0143] Step 103, according to the mean value μ of the disease surveillance data in the time window corresponding to each time point i i and stan...

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Abstract

A disease abnormality data detecting method comprises steps of: acquiring disease monitoring data from a time point 0 to a time point t to form time series data; selecting a time window size w for each time point i from the time point w to the time point t, and calculating the mean and standard deviation of the disease monitoring data in the time window corresponding to the time point i; calculating the moving-zscore value of the disease monitoring data corresponding to the time point i according to the mean and standard deviation of the disease monitoring data in the time window correspondingto each time point i, and obtaining an mz listz; determining an abnormal value threshold of the time series data according to the mz list; if the moving-zscore value of the disease monitoring data corresponding to the time point i is greater than the abnormal value threshold, determining the disease monitoring data corresponding to the time point i to be an abnormal value. The invention also provides a disease abnormality data detecting device, a computer device and a readable storage medium. The invention can realize high-efficiency and accurate abnormality detection of disease monitoring data.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and device for detecting abnormal disease data, 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 detect abnormal disease data, so as to be able to identify the epidemic or outbreak of public health emergencies early, take corresponding control measures as soon as po...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/80
CPCG16H50/80
Inventor 阮晓雯徐亮肖京
Owner PING AN TECH (SHENZHEN) CO LTD
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