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Health intervention scheme personalized recommendation method and system based on time sequence early warning signal

A health intervention and program technology, applied in the field of health care, can solve problems such as inaccurate results, lack of dynamic recommendation programs, and does not consider the individual physical characteristics of patients, so as to achieve the effect of improving accuracy

Active Publication Date: 2021-11-12
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the present invention provides a method and system for personalized recommendation of health intervention schemes based on time-series early warning signals, which solves the problem that the health intervention schemes recommended in the prior art do not consider the individual physical characteristics of patients and recommend The problem of inaccurate results caused by the lack of dynamics and continuity of the plan

Method used

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  • Health intervention scheme personalized recommendation method and system based on time sequence early warning signal
  • Health intervention scheme personalized recommendation method and system based on time sequence early warning signal
  • Health intervention scheme personalized recommendation method and system based on time sequence early warning signal

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Embodiment 1

[0062] In the first aspect, the present invention first proposes a personalized recommendation method for health intervention schemes based on time series early warning signals, see figure 1 , the method includes:

[0063] S1. Obtain user health data and preprocess the user health data;

[0064] S2. Based on the preprocessed user health data, obtain a user item rating matrix and a preference matrix of Tag label attributes;

[0065] S3. Based on the user-item scoring matrix and the preference matrix of Tag label attributes, use the SVD collaborative filtering algorithm to obtain a preliminary recommendation scheme set;

[0066] S4. Using the BP-DS neural network to locally adjust the set of preliminary recommendation schemes to obtain a complete recommendation scheme;

[0067] S5. Dynamically update the complete recommendation scheme based on the sequential update data generated by executing the complete recommendation scheme.

[0068] It can be seen that the technical solut...

Embodiment 2

[0200] In the second aspect, the present invention also discloses a personalized recommendation system for health intervention programs based on time series early warning signals, the system includes:

[0201] A data acquisition and preprocessing module, configured to acquire user health data and preprocess the user health data;

[0202] A data reprocessing module, configured to obtain a user-item rating matrix and a preference matrix for Tag label attributes based on the preprocessed user health data;

[0203] A preliminary recommendation scheme generation module is used to obtain a preliminary recommendation scheme set based on the user item rating matrix and the preference matrix of the Tag label attribute, using the collaborative filtering algorithm of SVD

[0204] A complete recommendation scheme generating module, configured to use the BP-DS neural network to locally adjust the set of preliminary recommendation schemes to obtain a complete recommendation scheme.

[0205...

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Abstract

The invention provides a health intervention scheme personalized recommendation method and system based on a time sequence early warning signal, and relates to the technical field of health medical treatment. According to the technical scheme, after the obtained user health data are preprocessed and reprocessed, the user item scoring matrix and the preference matrix of the Tag attribute are constructed based on the data, and then the preliminary recommendation scheme set of the health intervention scheme is obtained by using an SVD collaborative filtering algorithm, finally, the preliminary recommendation scheme set is locally adjusted by using a BP-DS neural network to obtain a complete recommendation scheme, and time sequence update data generated when the complete recommendation scheme is executed is returned to the previous process to update the data, thereby dynamically updating the complete recommendation scheme. According to the technical scheme, an accurate, reliable, complete, continuous and dynamic recommendation scheme can be provided for the user, and the accuracy of health monitoring is improved to a certain extent.

Description

technical field [0001] The invention relates to the technical field of health care, in particular to a method and system for personalized recommendation of health intervention schemes based on time series early warning signals. Background technique [0002] Patients will generate a large amount of health and medical information data in the process of treatment, rehabilitation, and life. Through the analysis and processing of relevant health and medical information data, and the use of relevant data analysis technology to analyze the user's physical characteristics, it can accurately find disease clues and Health hazards, and then generate recommended intervention programs and provide related services, and these personalized medical recommendation programs and services can provide patients with targeted and personalized medical services that meet the patient's personal characteristics, making the treatment and rehabilitation of patients more accurate and effective . [0003]...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H20/00G16H20/10G16H20/30G06F16/9536G06F40/289G06N3/08G06N3/04G06K9/62
CPCG16H20/00G16H20/10G16H20/30G06F16/9536G06F40/289G06N3/084G06F2216/03G06N3/048G06N3/045G06F18/25G06F18/257Y02A90/10
Inventor 顾东晓刘一莹李敏王晓玉赵旺鲍超骆辉魏亚龙杨雪洁苏凯翔
Owner HEFEI UNIV OF TECH