Method and device for evaluating curative effect of chronic diseases

A technology for efficacy evaluation and chronic diseases, applied in the field of bioinformatics, it can solve the problems of huge and complicated patient data, obstacles to analysis and judgment of chronic diseases, and large errors.

Active Publication Date: 2018-06-01
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology

[0004] At present, the existing traditional methods for evaluating the efficacy of chronic diseases are to set up a control group or compare before and after treatment, and then use statistical methods such as t-test or chi-square test to investigate the efficacy of drugs. diseases, and the analysis results are rough, general, and have large errors, and the reliability of the analysis results is low due to the large and complicated data of some patients, which has caused huge obstacles to the analysis and judgment of medical workers on the treatment plan of patients with chronic diseases

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  • Method and device for evaluating curative effect of chronic diseases
  • Method and device for evaluating curative effect of chronic diseases
  • Method and device for evaluating curative effect of chronic diseases

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Embodiment 1

[0062] refer to figure 2 , the first embodiment of the present invention provides a method for evaluating the curative effect of drugs for chronic diseases, including:

[0063] Step S1, determine the clustering method;

[0064] As mentioned above, what needs to be understood is that cluster analysis, also known as group analysis, is a statistical analysis method for studying (samples or indicators) classification problems, and it is also an important algorithm for data mining. Cluster analysis is composed of several patterns. Usually, a pattern is a vector of a measurement, or a point in a multidimensional space. Cluster analysis is based on similarity, with more similarities between patterns within a cluster than patterns not within the same cluster.

[0065] As mentioned above, clustering methods include multiple categories such as partition-based clustering, hierarchical clustering, density-based clustering, and model-based clustering.

[0066] As mentioned above, in th...

no. 1 example

[0074] The S1 includes:

[0075] S11, generating simulation data conforming to the statistical characteristics of the real feature data according to the real feature data of the case;

[0076] In this embodiment, the clustering method is selected by means of model Carlo simulation.

[0077] As mentioned above, it needs to be understood that the Monte Carlo method, also known as random sampling or statistical test method, belongs to a branch of computational mathematics, which was developed in the mid-1940s to adapt to the development of the atomic energy industry at that time. of. Because the traditional empirical method cannot approach the real physical process, it is difficult to obtain satisfactory results, while the Monte Carlo method can truly simulate the actual physical process, so the solution to the problem is very consistent with the actual situation, and very satisfactory results can be obtained. This is also a method of computing based on the theoretical methods ...

Embodiment 3

[0091] refer to Figure 5 , the third embodiment of the present invention provides a chronic disease drug curative effect evaluation method, based on the above image 3 In the second embodiment shown, the S12 includes:

[0092] S121, determine the category of the clustering method;

[0093] S122. Select one or more clustering methods in each category;

[0094] As mentioned above, clustering methods are divided into multiple categories such as partition-based clustering, hierarchical clustering, density-based clustering, and model-based clustering, and one or more methods are selected from each category to cluster the simulation data. , including but not limited to K-Means, K-MEDOIDS, BIRCH, CURE, DBSCAN, STING, etc.

[0095] S123. Cluster the simulation data by using different clustering methods, and generate clustering result information corresponding to the clustering methods.

[0096] Since there is no external label information for clustering in this scenario, the inte...

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Abstract

The invention provides a method and device for evaluating the efficacy of a chronic disease drug. The method includes the steps of determining a clustering method; clustering real feature data of a case according to the clustering method, and obtaining drug use information and diagnostic information corresponding to different categories; and analyzing the efficacy of each drug according to the drug use information and diagnostic information corresponding to the different categories. The method provided by the invention can be applied to the theoretical research related to the evaluation of theefficacy of the chronic disease drug, and can also be applied to the prediction, early warning and drug recommendation of the clinical disease complications simultaneously. The analysis results are detailed, accurate, small in error. The larger the number of data samples is, the greater the credibility of the analysis results is. Great convenience is brought to medical workers in analyzing and judging the treatment of chronic diseases. The method is of great significance for the analysis of biological and medical related fields.

Description

technical field [0001] The invention relates to the technical field of biological information, and more specifically, to a method and device for evaluating curative effect of chronic disease drugs. Background technique [0002] The full name of chronic disease is chronic non-communicable disease. It does not refer to a certain disease, but to a class of insidious onset, long course of disease and protracted disease, lack of definite evidence of infectious biological etiology, complex etiology, and some have not been fully recognized. A general term for a recognized disease. Common chronic diseases mainly include cardiovascular and cerebrovascular diseases, cancer, diabetes, and chronic respiratory diseases. Cardiovascular and cerebrovascular diseases include hypertension, stroke and coronary heart disease. [0003] In 2012, the national prevalence rate of hypertension among adults aged 18 and over was 25.5%, and the prevalence rate of diabetes was 9.7%. According to the an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G16H70/40
Inventor 王莹莹张剑冬李奇蔡云鹏
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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