Diagnosis and treating rules mining method based on Boolean matrix

A Boolean matrix and rule technology, applied in the computer field, can solve problems such as inability to express diagnosis and treatment rules, algorithm efficiency needs to be improved, and does not solve the problems of large number of candidate item sets and frequent database scanning, etc., to save storage space, mine efficiently, and overcome multiple times The effect of too many scans and candidate frequent itemsets

Active Publication Date: 2015-07-08
XIDIAN UNIV
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Problems solved by technology

However, the disadvantage of this method is that this method mines association rules for plant and animal data sets of molecular genetic markers, and the data structure of the "feature data set" established cannot reasonably and effectively analyze the diagnosis and treatment rules. Representation is not conducive to the use, sharing, maintenance and updating of medical

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  • Diagnosis and treating rules mining method based on Boolean matrix
  • Diagnosis and treating rules mining method based on Boolean matrix

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Experimental program
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Embodiment Construction

[0027] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0028] Step 1, structure design of diagnosis and treatment rules.

[0029] Scan the transaction database that stores the basic data of diagnosis and treatment, and map the transaction database into a Boolean matrix according to the mapping rules. Among them, the mapping rule means that the number of rows of the Boolean matrix is ​​the same as the number of transaction sets, and the number of columns of the Boolean matrix is ​​the same as the number of items contained in each transaction set; The value of the column corresponding to the item in the row of the transaction set is 1, otherwise it is 0.

[0030] Step 2, mining diagnosis and treatment rules.

[0031] The association rule mining method based on Boolean matrix is ​​used to obtain the frequent itemsets of the medical affairs database.

[0032] Divide the data items in each frequent item set into ru...

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Abstract

The invention discloses a diagnosis and treating rules mining method based on Boolean matrix. The method comprises the steps: 1, acquiring basic diagnosis and treating data; 2, mining diagnosis and treating rules; 3, setting parameters of diagnosis and treating rules; judging whether the setting of all parameters of the diagnosis and treating rules are completed or not; if yes, performing step 5; or else, performing the step 3; 5, performing structuralized modeling on the diagnosis and treating rules; 6, storing diagnosis and treating rules data. The structuralized modeling is performed on the diagnosis and treating rules, thus presentation and storage structures of the diagnosis and treating rules are standardized; meanwhile, the Boolean maxis is applied to the diagnosis and treating rules mining method, thus the mining of the diagnosis and treating rules are efficient and more storage space is saved.

Description

technical field [0001] The invention belongs to the field of computer technology, and further relates to a method for mining diagnosis and treatment rules based on a Boolean matrix. The invention uses an association rule mining method based on a Boolean matrix to explore attention-worthy associations and correlations among a large number of data items, and digs out frequently used rule sets as the driving force of the rule engine. As an important part of decision support system, rule engine can assist doctors to make accurate and comprehensive decisions in clinical diagnosis and treatment activities. Background technique [0002] With the advent of the era of big data, the traditional rule extraction scheme can no longer meet the basic needs of complex analysis and processing of a large amount of medical data to obtain valuable decision-making information. Moreover, due to the unstructured and semi-structured non-standard and non-uniform description forms of the rules, a se...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F19/00
Inventor 李青山褚华王璐徐永飞魏鸿鹏魏雨旸杨志福
Owner XIDIAN UNIV
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