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Meta analysis generation method based on artificial intelligence

An artificial intelligence and artificial technology, applied in the field of modern medicine, can solve problems such as low efficiency and large workload, and achieve the effect of reducing workload, improving efficiency, and reducing wasted time.

Active Publication Date: 2020-08-18
周敬洋
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] For this reason, the object of the present invention is to provide a kind of Meta-analysis generation method based on artificial intelligence, be used to solve the problem that data exists limitation, inefficiency and heavy workload in the Meta-analysis that prior art exists

Method used

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  • Meta analysis generation method based on artificial intelligence

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Embodiment 1

[0062] Such as figure 1 As shown, the present embodiment provides a method for generating Meta analysis based on artificial intelligence, comprising the following steps:

[0063] S1. Obtain the topic, extract the keywords of the topic based on artificial intelligence, and supplement the keywords. The specific steps are:

[0064] S1-1. According to the existing Meta analysis data, based on artificial intelligence machine learning, establish a keyword retrieval model;

[0065] S1-2. Obtain the title, use the keyword retrieval model to perform feature extraction, and obtain the keywords of the title;

[0066] S1-3. Based on the medical database, in the present embodiment, first call the MeSH function on the PubMed website by itself, retrieve the synonyms of the keywords, obtain the corresponding phrase set, and sort in descending order according to the frequency of occurrence of the result words in the phrase set ;

[0067] S1-4. Supplement the keywords of the top 50% of the r...

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Abstract

The invention belongs to the technical field of modern medicine, and discloses a Meta analysis generation method based on artificial intelligence, which comprises the following steps of S1, obtainingquestions, extracting keywords, and supplementing the keywords; S2, performing Meta analysis to obtain an initial literature set, and performing topic selection evaluation and self duplicate checkingto obtain a final literature set; s3, acquiring an in-row standard, and screening to obtain a reference literature set; s4, performing quality evaluation; s5, performing data extraction on all literatures in the reference literature set to obtain an experimental data set; s6, obtaining corresponding experimental data from the experimental data set according to preset experimental information, andobtaining a reference conclusion according to the experimental data; and S7, according to the preset literature format requirement and the reference conclusion, obtaining a reference literature, and completing Meta analysis. According to the invention, the problems of data limitation, low efficiency and large workload in Meta analysis in the prior art are solved.

Description

technical field [0001] The invention belongs to the technical field of modern medicine, and in particular relates to an artificial intelligence-based Meta analysis generation method. Background technique [0002] At present, the latest development of evidence-based medicine is the application of Meta-analysis. Meta-analysis integrates as many existing literatures as possible, and analyzes the data collected from clinical trials or case reports based on statistical methods. Use the data obtained from a large sample to resolve the existing controversies in current medicine. [0003] Meta-analysis, also known as "Meta-analysis", Meta means a more comprehensive thing that appeared later, and is usually used to name a new related and commentary on the original discipline, including not only data combination, but also results In epidemiological exploration and evaluation, the findings of original research replace individuals as analytical entities. [0004] Machine learning of a...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/335G06F40/247G06N20/00
CPCG06F16/3334G06F16/335G06N20/00G06F40/247
Inventor 周敬洋
Owner 周敬洋