Apriori-based disease data association method

A technology of data association and disease, which is applied in the direction of electrical digital data processing, medical data mining, special data processing applications, etc., can solve problems that have not been applied in the medical field, achieve the optimization of disease diagnosis editing, improve accuracy and efficiency Effect

Inactive Publication Date: 2018-09-18
KUNMING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

Moreover, the algorithm has been widely used in various fields such as business and network security, but it has not been applied to the medical field.

Method used

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  • Apriori-based disease data association method
  • Apriori-based disease data association method
  • Apriori-based disease data association method

Examples

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Embodiment 1

[0024] Embodiment 1: as Figure 1-4 Shown, a kind of disease data association method based on Apriori comprises the following steps:

[0025] Step1, establish disease keyword database;

[0026] Step2. Carry out word segmentation processing on the applicable symptom text of the drug through the keywords in the established disease keyword database, and extract the disease keywords of the applicable symptoms;

[0027] Step3. Introduce the Apriori algorithm, the set of all drugs is D, and each disease keyword is used as a candidate item set c 1 , the i-th candidate 1-itemset is denoted as c 1 (i), whose set is C 1 , set a minimum support threshold min_sup, when c 1 The support count support_count(c 1 ) is greater than or equal to min_sup, then c 1 become a frequent 1-itemset l 1 , all l 1 The set of L 1 , by adding L 1 Connect with itself to generate candidate 2-itemset c 2 , all c 2 set of C 2 , if C 2 The i-th candidate 2-itemset c in 2 A certain subset of (i) is ...

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Abstract

The invention relates to an Apriori-based disease data association method, which belongs to the technical field of data mining and recommendation. The Apriori-based disease data association method comprises the steps of: firstly, establishing a disease keyword database; secondly, carrying out word segmentation processing on an applicable symptom text of a drug by adopting a conventional word segmentation program on the basis of the established disease keyword database, extracting keywords of applicable symptoms, regarding each keyword as a candidate 1 item set, and introducing an Apriori algorithm to calculate frequent item sets of different item numbers; secondly, generating corresponding strong association rules by each frequent item set, and calculating a confidence degree of each strong association rule; and finally, performing recommendation sorting on the frequent item sets according to confidence degrees of the strong association rules. Compared with the prior art, the Apriori-based disease data association method mainly provides the Apriori algorithm to play an association recommendation role in diagnosis and editing of diseases, and improves the accuracy and efficiency inediting the symptoms when a doctor writes out a prescription.

Description

technical field [0001] The invention relates to an Apriori-based disease data association method, which belongs to the technical field of data mining recommendation. Background technique [0002] At present, modern medical technology has made great progress. However, the complexity of associations and names of various diseases also caused some interference and influence on doctors' disease diagnosis and editing results. [0003] Apriori algorithm is a frequent itemset algorithm for mining association rules. Its core idea is to mine frequent itemsets through two stages of candidate set generation and downward closure detection of episodes. Moreover, algorithms have been widely used in various fields such as business and network security, but have not yet been applied to the medical field. Contents of the invention [0004] The technical problem to be solved by the present invention is an Apriori-based disease data association method. The Apriori algorithm is applied to th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H70/40G16H20/13G16H50/70G06F17/30G06F17/27
CPCG16H20/13G16H50/70G16H70/40G06F40/289
Inventor 宋耀莲田榆杰王慧东徐文林武双新
Owner KUNMING UNIV OF SCI & TECH
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