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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 the problems of inaccurate, difficult to determine, and difficult to determine the patient's influence weight, etc., and achieve good historical medical records. , the effect of improving the accuracy

Active Publication Date: 2020-07-28
SHANDONG UNIV
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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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  • Patient similarity analysis method and system based on improved heterogeneous information network
  • Patient similarity analysis method and system based on improved heterogeneous information network
  • 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

The invention provides a patient similarity analysis method and system based on an improved heterogeneous information network. The method comprises the steps: taking hospitalization information of a patient as data input, constructing an annotation heterogeneous information network, and associating relationships among patients, diseases and drugs; constructing a meta-structure by taking the expanded structure of the annotation heterogeneous information network as a directed graph of a template; and based on the meta-structure, carrying out similarity calculation to obtain similarity. Accordingto the invention, annotation of patient information is added in connection of diseases and medicines, so that the problem that associated information between patients and medicines is lost in a classical heterogeneous information network is solved, and historical medical records can be well associated; and the relationship among the patient, the disease and the medicine is associated, so that theaccuracy of patient similarity calculation is improved.

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...

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Application Information

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Patent Type & Authority Applications(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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