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Knowledge graph construction and use method and device and medium

A knowledge map and user technology, applied in the medical field, can solve problems such as difficult to accurately distinguish various diseases, and achieve the effect of improving the degree of discrimination

Pending Publication Date: 2021-05-04
BEIJING SOGOU TECHNOLOGY DEVELOPMENT CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the process of implementing the embodiment of the present invention, the inventor found that it is difficult to accurately distinguish multiple diseases when the existing knowledge map is used to match the symptoms of the user

Method used

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  • Knowledge graph construction and use method and device and medium
  • Knowledge graph construction and use method and device and medium
  • Knowledge graph construction and use method and device and medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0078] In the embodiment of the present invention, the knowledge graph is a structured semantic knowledge base, which is used to describe concepts and their relationships in the physical world.

[0079] In the embodiments of the present invention, an entity (Entity) refers to an objectively existing and mutually distinguishable transaction, including a specific person, thing, thing, abstract concept or connection, and the like. An entity can be a specific object, such as a disease, a disease characteristic, etc.; it can also be an abstract event, such as a consultation for a disease characteristic.

[0080] Entities can have many properties, and individual properties are called attributes. Each attribute has a value field, and its type can be integer type, real number type, or string type, etc. The named unit of a tag property is called a field. The state of the field may include: a filled state or an unfilled state, wherein the filled state corresponds to filled field conte...

Embodiment 2

[0141] An embodiment of a method for constructing a knowledge map of the present invention may specifically include:

[0142] In the knowledge map, establish the association between the disease characteristic entity and the disease entity;

[0143] Wherein, the attributes of the above-mentioned disease entity specifically include at least one of the following attributes: disease identification attribute, disease system attribute, feature set attribute, clinical proportion attribute, and high incidence age attribute;

[0144] The above feature set may include: the disease feature associated with the above disease feature entity; the attribute parameters of the above feature set attribute include: the conditional probability of the disease feature under the condition of the disease, and / or, the conditional probability of the disease feature under the condition of the disease penalty factor;

[0145] The above clinical proportion attribute is used to represent the incidence prob...

Embodiment 3

[0176] An embodiment of a method for constructing a knowledge map of the present invention may specifically include:

[0177] In the knowledge map, establish the association between the disease characteristic entity and the disease entity;

[0178] Determining a problem entity according to the disease characteristic entity; the problem entity is used to represent a problem related to the disease characteristic entity;

[0179] In the knowledge map, establish the association between the disease feature entity and the problem entity;

[0180] Wherein, the attributes of the above-mentioned disease entity specifically include at least one of the following attributes: disease identification attribute, disease system attribute, feature set attribute, clinical proportion attribute, and high incidence age attribute;

[0181] The above-mentioned feature set includes: the disease feature associated with the above-mentioned disease feature entity; the attribute parameters of the above-m...

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Abstract

The embodiment of the invention provides a knowledge graph construction and use method and devic and a medium. The method comprises the following steps: establishing association between disease feature entities and disease entities in a knowledge graph, the attributes of the disease entity comprise at least one of the following attributes: a disease identification attribute, a disease system attribute, a feature set attribute, a clinical proportion attribute and a high-incidence age attribute; the feature set comprises disease features associated with disease feature entities; the attribute parameters of the feature set attributes comprise conditional probabilities of the disease features under disease conditions and / or penalty factors of the disease features under the disease conditions; the clinical proportion attribute is used for representing the incidence probability of a disease in a disease system; the disease system attribute corresponds to a system probability and is used for representing the proportion of a patient of a single disease system to patients of all disease systems. According to the embodiment of the invention, the distinction degree among various diseases matched with the disease characteristics of the user can be improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of medical technology, and in particular to a method, device and medium for constructing and using a knowledge map. Background technique [0002] The disease prediction process is based on the user's symptoms to infer the risk of a possible disease or clinical event. With the popularity of the Internet and the increase of medical resources, more and more users obtain information about possible diseases through the Internet. [0003] The current method of using knowledge graphs usually uses knowledge graphs to connect trivial and scattered medical information knowledge to each other, and applies knowledge graphs to disease prediction processing. Specifically, the knowledge graph usually includes the edge relationship between the disease entity and the symptom entity, so that according to the above edge relationship, the corresponding disease can be predicted for the user's symptoms. [0004]...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/28G16H50/20G16H50/30
CPCG06F16/367G06F16/288G16H50/30G16H50/20
Inventor 何峻青
Owner BEIJING SOGOU TECHNOLOGY DEVELOPMENT CO LTD
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