Human-computer collaborative health case matching method and system based on chronic disease big data

A human-machine collaboration and big data technology, applied in the field of data processing, can solve problems such as inaccurate matching results, and achieve the scientific effect of solving inaccurate matching results, scientific and accurate recommendation results, and human-machine collaborative health case matching technology

Active Publication Date: 2022-06-17
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0006] Aiming at the deficiencies of the existing technology, the present invention provides a human-computer collaborative health case matching method and system based on chronic disease big data, which solves the problem of inaccurate matching results in health case matching in the prior art

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  • Human-computer collaborative health case matching method and system based on chronic disease big data
  • Human-computer collaborative health case matching method and system based on chronic disease big data
  • Human-computer collaborative health case matching method and system based on chronic disease big data

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Embodiment 1

[0053] In the first aspect, the present invention first proposes a human-machine collaborative health case matching method based on chronic disease big data, the method includes:

[0054] S1. Obtain multi-modal time series medical health data based on multi-channel;

[0055] S2. Preprocess the time series medical and health data, and determine the data characteristics in combination with the doctor's annotation;

[0056] S3. Extract key features based on the data features, and combine guidelines, standard procedures, classic cases and doctor's expert knowledge to build a knowledge base of health cases;

[0057] S4, fusing the multi-modal data features based on the multi-modal fusion method to obtain the user's health evaluation index;

[0058] S5. Obtain the eigenvalue sequence similarity between the current case and the eigenvalue sequence of the classic case in the above-mentioned health case knowledge base based on the feature similarity calculation algorithm;

[0059] S6...

Embodiment 2

[0086] In the second aspect, the present invention also proposes a human-machine collaborative health case matching system based on chronic disease big data, see Figure 4 , the system includes:

[0087] The data acquisition module is used to acquire multi-modal time series medical health data based on multi-channel;

[0088]a data preprocessing module, which is used to preprocess the time series medical and health data, and determine the data characteristics in combination with the doctor's annotation;

[0089] The case knowledge base building module is used to extract key features based on the data features, and combine guidelines, standard procedures, classic cases and doctor expert knowledge to build a health case knowledge base;

[0090] a health status evaluation module, used to fuse the multi-modal data features by using a multi-modal fusion method to obtain the user's health evaluation index;

[0091] The eigenvalue sequence similarity calculation module is used to o...

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Abstract

The invention provides a human-computer collaborative health case matching method and system based on chronic disease big data, and relates to the technical field of data processing. The present invention firstly fuses the user's dynamic time-sequential medical health data from multi-channel and multi-modal, and extracts the features of these dynamic time-sequential medical health data, and then combines the doctor's expert knowledge to select the features, and then analyzes the data from different modalities. The data features are fused, and the weights are assigned to the feature indicators. Combined with the normalized features of the preprocessing module, linear weighting is performed to obtain the health evaluation index, and then the feature similarity calculation algorithm is used to obtain the current case and the classic case in the above-mentioned health case knowledge base. The similarity of the eigenvalue sequence of the eigenvalue sequence, and finally generate a personalized health recommendation plan for the user according to the health evaluation index and the similarity of the eigenvalue sequence. This technical solution solves the problem of inaccurate matching results in health case matching in the prior art.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a human-machine collaborative health case matching method and system based on chronic disease big data. Background technique [0002] With the aging of my country's population, the prevention and treatment of chronic diseases has become a major social problem in my country in the new era. At the same time, the further advancement of medical informatization has gradually increased the scale of medical information resources, resulting in massive medical and health data; while natural language processing technology, image, audio and video processing technology, and multimodal data fusion technology continue to move forward The development provides technical support for the fusion of multi-channel and multi-modal medical and health data. How to make full use of these resources to provide personalized health evaluation methods for chronic disease users has become a future res...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/30G16H50/20G16H50/70G06F16/903
CPCG16H50/30G16H50/20G16H50/70G06F16/903
Inventor 顾天阳
Owner BEIJING UNIV OF POSTS & TELECOMM
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