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A patient similarity analysis method and system based on improved heterogeneous information network

A heterogeneous information network and similarity analysis technology, applied in the field of patient similarity analysis based on improved heterogeneous information network, can solve problems such as difficulty in determining, different patient influence, and imprecise similarity.

Active Publication Date: 2021-05-11
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, there are several problems with clinical indicators. First, there are many kinds of clinical indicators, and the impact of changes in clinical indicators on patients is also different. It is difficult to determine which clinical indicators can best characterize patients. Second, the impact of different clinical indicators on patients The influence is different, and it is difficult to determine the impact weight of different clinical indicators on patients
Therefore, the calculated similarity is inaccurate

Method used

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  • A patient similarity analysis method and system based on improved heterogeneous information network
  • A patient similarity analysis method and system based on improved heterogeneous information network
  • A patient similarity analysis method and system based on improved heterogeneous information network

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Embodiment Construction

[0034] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0035] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0036] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

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Abstract

This disclosure provides a patient similarity analysis method and system based on an improved heterogeneous information network, which takes patient hospitalization information as data input, constructs an annotation heterogeneous information network, and associates the relationship among patients, diseases, and drugs; The expanded structure of the structural information network is a directed graph of the template, and the meta-structure is constructed; based on the meta-structure, the similarity calculation is performed to obtain the similarity. In the connection between diseases and drugs, the annotation of patient information is added, which solves the problem of missing the associated information between patients and drugs in the classic heterogeneous information network, and can also link historical medical records very well; associate patients, diseases, and drugs The relationship between the three improves the accuracy of patient similarity calculation.

Description

technical field [0001] The disclosure belongs to the technical field of data similarity analysis, and in particular relates to a patient similarity analysis method and system based on an improved heterogeneous information network. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] The patient similarity analysis is based on the universal assessment of the distance between patients, and obtains the general law of disease development from a large amount of clinical practice data, thus making it possible to use a general computer-aided clinical decision support framework to achieve personalized diagnosis and treatment. Generally speaking, patient similarity analysis refers to the selection of clinical concepts (such as diagnosis, symptoms, examinations, family history, past history, exposure environment, drugs, surgery, genes, etc.) as characte...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/20G16H50/70G16H70/40G06K9/62
CPCG16H50/20G16H50/70G16H70/40G06F18/22
Inventor 郭伟刘静刘斌鹿旭东崔立真
Owner SHANDONG UNIV
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