A method for evaluating hypertension risk based on mixed guidance of time-frequency components

By using the time-frequency component mixed guidance method in the risk assessment of hypertension, an initial model containing the time-frequency component and frequency component mixing module is constructed, which solves the problems of high parameter quantity and overfitting in the prior art, and achieves a more efficient and accurate risk assessment of hypertension.

CN118571488BActive Publication Date: 2025-04-01SHENZHEN UNIV +1
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Patent Information

Application Number
CN202411026040.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-07-30
Publication Date
2025-04-01
Estimated Expiration
2044-07-30

AI Technical Summary

Technical Problem

In the evaluation of hypertension risk, the high amount of parameters in the model design leads to strong coupling between the data and the model, overfitting problems, poor general ability, low prediction accuracy, and high training cost.

Method used

Using a time-frequency component hybrid guidance method, an initial model including a time-component mixing module, a frequency-component mixing module, a feature enhancement module and a prediction module is constructed. The network parameters are reduced in the time-frequency domain through a parameterless component extraction strategy to achieve decoupling of data and model.

Benefits of technology

It effectively reduces network parameters, reduces model complexity, improves prediction accuracy, reduces training costs, and achieves a more comprehensive and accurate risk assessment of hypertension.

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Abstract

The present invention discloses a hypertension risk assessment method based on time-frequency component mixed guidance. The method comprises: constructing an initial model, the initial model comprises a time component mixed module, a frequency component mixed module, a feature enhancement module and a prediction module; obtaining an initial data set, the initial data set is a time series data set of multiple hypertensive patients; training the initial model based on the initial data set to obtain a target prediction model; obtaining target data, predicting the target data based on the target prediction model, and obtaining a hypertension risk prediction result for the target patient, the target data is hypertension-related data of the target patient, and there are multiple target patients. The hypertension risk assessment method based on time-frequency component mixed guidance provided by the present invention can effectively reduce network parameters by designing a parameter-free component extraction module and a feature enhancement module, thereby achieving the effect of decoupling data from the model, and can more accurately predict the patient's hypertension risk.
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