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Medical expert personalized recommendation method and system based on big data verification

A technology of medical experts and recommended methods, applied in the medical field, can solve problems such as patients being unable to find, achieve the effect of improving the accuracy of medical treatment, solving asymmetric contradictions, and realizing personalized medical treatment

Inactive Publication Date: 2017-01-04
广州比特软件科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In view of this, in order to solve the technical problem that patients cannot find the most suitable medical experts in the prior art, the present invention proposes a method and system for personalized recommendation of medical experts based on big data verification, making full use of Internet information, through big data methods , establish a set of technologies and algorithms, establish personalized expert recommendations from experts' professional expertise, service quality and individual needs of patients, make full and reasonable use of medical resources, and improve patient diagnosis and treatment effects

Method used

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  • Medical expert personalized recommendation method and system based on big data verification
  • Medical expert personalized recommendation method and system based on big data verification
  • Medical expert personalized recommendation method and system based on big data verification

Examples

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Embodiment 1

[0082] like figure 1 , figure 2 As shown, a personalized recommendation method for medical experts based on big data verification includes the following steps:

[0083] S1. Establish a medical expert database, which includes expert personal data, patient evaluation data on experts, and hospital data;

[0084] Specifically include the following steps:

[0085] S11. Collect personal data of experts through the portal websites of each hospital;

[0086] S12. Modify and improve the personal data after the expert himself is authenticated;

[0087] S13. Obtain patient evaluation data on experts through a third-party website;

[0088] S14. Obtain hospital information through the hospital website;

[0089] Expert personal information includes expert basic information, education background, degree, academic title, professional title, position, tutor qualification, expertise, education experience, work experience, publications, topics obtained, achievements, awards, and academic a...

Embodiment 2

[0127] like image 3 As shown, a medical expert personalized recommendation system based on big data verification includes a medical expert database, the medical expert database includes expert personal data database, patient evaluation data database, hospital data database, and also includes expert personal data verification module, expert specialty recommendation calculation module, patient-to-expert evaluation data verification module, hospital data verification module, expert specialty recommendation model storage module, patient information acquisition module, personalized demand model storage module, and personalized recommendation module;

[0128] The expert personal data database, the expert personal data verification module, and the expert specialty recommendation degree calculation module are sequentially connected;

[0129] The patient-to-expert evaluation data database is connected to the patient-to-expert evaluation data verification module;

[0130] The hospital...

Embodiment 3

[0146] like Figure 4 As shown, a medical expert personalized recommendation system based on big data verification includes a medical expert database, the medical expert database includes expert personal data database, patient evaluation data database, hospital data database, and also includes expert personal data verification module, expert specialty recommendation calculation module, patient-to-expert evaluation data verification module, hospital data verification module, expert specialty recommendation model storage module, patient information acquisition module, personalized demand model storage module, and personalized recommendation module;

[0147] The expert personal data database, the expert personal data verification module, and the expert specialty recommendation degree calculation module are sequentially connected;

[0148] The patient-to-expert evaluation data database is connected to the patient-to-expert evaluation data verification module;

[0149] The hospita...

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Abstract

The invention discloses a medical expert personalized recommendation method and system based on big data verification. The method includes the steps: S1, building a medical expert database comprising expert personal data, expert evaluating data of patients and hospital data; S2, verifying personal data of experts in many ways by the aid of a big data method; S3, computing special recommendation degrees of the experts; S4, verifying expert data evaluated by patients by the aid of a big data method; S5, verifying hospital data by the aid of a big data method; S6, comprehensively building special recommendation models of the experts according to the three aspects; S7, acquiring patient information; S8, building personalized requirement models according to the patient information; S9, individually recommending the medical experts according to the special recommendation models of the experts and the personalized requirement models. The medical expert personalized recommendation method solves the problem of asymmetric information between doctors and patients, medical advice seek accuracy of the patients is improved, medical resources are sufficiently and reasonably used, medical advice seeking personalization is achieved, and clinical effects are improved.

Description

technical field [0001] The invention relates to the field of medical technology, in particular to a medical expert personalized recommendation method and system based on big data verification. Background technique [0002] The treatment effect of patients is affected by many factors, among which finding the most suitable specialist is the most important factor. [0003] Because patients do not understand medical knowledge, do not understand the expertise of medical institutions and experts, they are often in a blind and passive state when choosing an expert. This information asymmetry seriously affects the patient's medical treatment effect. A disease that is not one's own expertise is also a waste of experts, who do not give full play to their expertise and affect the quality of medical care. [0004] There are differences in the technical level of different hospitals. Different hospitals have different specialty departments. In the same hospital, there are differences in ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
CPCG16H40/20
Inventor 秦建增
Owner 广州比特软件科技有限公司
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