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Data matching method and related equipment thereof

A matching method and matching relationship technology, applied in the field of data analysis, can solve problems such as inaccurate research and analysis results, and achieve the effect of increasing the amount of data, avoiding adverse effects, and improving accuracy

Pending Publication Date: 2021-11-16
NEUSOFT CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] However, due to the flaws in the related data matching technology, the medical data matching pairs determined by the related data matching technology also have defects in some special scenarios (such as the above-mentioned scenarios where the data volume of the two sets of medical data is inconsistent, etc.), so it is easy to cause Subsequent analyzes based on these medical data matching pairs identified were inaccurate

Method used

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  • Data matching method and related equipment thereof
  • Data matching method and related equipment thereof
  • Data matching method and related equipment thereof

Examples

Experimental program
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Effect test

example 1

[0085] Example 1, based on the above assumptions, it can be known that the determination process of "the matching relationship between the r-th first medical data and at least one second medical data" may specifically include: if it is determined that the target data set includes the r-th first medical data and D r second medical data, then establish the r first medical data and the D r The matching relationship between each second medical data in a second medical data. Among them, D r is a positive integer.

[0086] It can be seen that after the above "at least one clustering data set" is obtained, the clustering data set including the rth first medical data can be found from the above "at least one clustering data set" (that is, the above "target data set"); and then establish a matching relationship between each second medical data in the clustering data set and the r first medical data to obtain at least one matching pair of medical data including the r first medical da...

example 2

[0087] Example 2, based on the above assumptions, in order to ensure that the similarity between the two medical data in each medical data matching pair is relatively high, the embodiment of the present application also provides "the rth first medical data and at least one second Another possible implementation of the determination process of the "matching relationship between medical data", which may specifically include step 11-step 12:

[0088] Step 11: If it is determined that the target data set includes the rth first medical data and D r second medical data, then from D r At least one target medical data is screened from the second medical data, so that the similarity between each target medical data and the r-th first medical data reaches a preset similarity condition.

[0089] Among them, the "preset similarity condition" refers to the condition that the similarity between two medical data in any medical data matching pair must be met; and the embodiment of this appli...

example 3

[0123] Example 3, the "preset extraction rule" may specifically include extracting a random number of data dimensions each time, and determining the set of the random number of data dimensions as a dimension target, until all "N data dimensions" are determined to be extracted end. Wherein, the "random number" is a numerical value (for example, 1, 2, 3 . . . ) randomly determined during each round of drawing.

[0124] It can be seen that, for the "T dimensional objects" determined based on the "preset extraction rules" in Example 3, the number of data dimensions included in different dimensional objects may be the same or may not be the same.

[0125] The "second clustering process" in S22 is used to refer to the process of clustering all the "first data sets" with reference to the data characteristics under certain data dimensions. It can be seen that the clustering object targeted in the "second clustering process" is the above-mentioned "first data set".

[0126] In additi...

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Abstract

The embodiment of the invention discloses a data matching method and related equipment, and the method comprises the steps: obtaining a first group of medical data with a lower data volume and a second group of medical data with a higher data volume, and then carrying out the preset clustering processing of the first group of medical data and the second group of medical data to obtain at least one clustering data set, so that the clustering data sets can accurately show that each first medical data in the first group of medical data and each second medical data in the second group of medical data belong to the same class; according to the at least one clustering data set, establishing a matching relationship between each first medical data and at least one second medical data under the clustering category to which the first medical data belongs, so that the one-to-many matching purpose can be realized, the data volume of the medical data matching pairs can be effectively improved, and the accuracy of research and analysis results is improved.

Description

technical field [0001] The present application relates to the technical field of data analysis, in particular to a data matching method and related equipment. Background technique [0002] In some medical research scenarios (for example, research on the cause of a certain disease), it is necessary to match two sets of medical data (for example, case group medical data and control group medical data); Data (hereinafter referred to as medical data matching pair) for research and analysis. [0003] However, due to the flaws in the related data matching technology, the medical data matching pairs determined by the related data matching technology also have defects in some special scenarios (such as the above-mentioned scenarios where the data volume of the two sets of medical data is inconsistent, etc.), so it is easy to cause Subsequent analysis of studies based on these medical data matching pairs identified inaccurate results. Contents of the invention [0004] In view of...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G06F16/906G06K9/62
CPCG16H50/70G06F16/906G06F18/22
Inventor 郑铭鑫曹延泽陆可韩宇吴迪
Owner NEUSOFT CORP
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