Cardiovascular system physiological age prediction method based on machine learning
By processing cardiovascular health data in a gender-based machine learning model and using blood pressure and heart rate indicators for physiological age prediction and correction, the problem of difficult to accurately reflect the physiological age and gender differences of different organs or systems in the prior art is solved, and a more accurate assessment of the physiological age of the cardiovascular system is achieved.
CN119964810APending Publication Date: 2025-05-09SHANGHAI SAIER XUMI INFORMATION TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202510135190.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-07
- Publication Date
- 2025-05-09
AI Technical Summary
Technical Problem
The prior art is difficult to accurately reflect the physiological age of different organs or systems of individuals, and a single model is difficult to deal with the differences in indicators between individuals of different genders.
Method used
Using a machine learning-based approach, cardiovascular health data for men and women were modeled separately, and physiological age prediction was performed using cardiovascular system-related blood pressure and heart rate indicators, and age correction was performed through linear regression.
Benefits of technology
Accurate assessment of the physiological age of the cardiovascular system in individuals of different genders is achieved, and the accuracy of prediction results is improved.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses a cardiovascular system physiological age prediction method based on machine learning, and the method comprises the steps: specifically collecting cardiovascular health data, carrying out the modeling of a computer model for male and female data according to the cardiovascular health data, building a computer model of a male and female cardiovascular system, and carrying out the prediction of the physiological age of the cardiovascular system. The method is used for evaluating physiological ages of cardiovascular systems of individuals with different genders. According to the cardiovascular system physiological age prediction method based on machine learning, core data is modeled only by using blood pressure and heart rate indexes related to the cardiovascular system, and the physiological age model of the cardiovascular system is constructed, so that the cardiovascular physiological age can be evaluated in a targeted manner; moreover, according to the cardiovascular system physiological age prediction method based on machine learning, modeling is carried out for men and women based on the data difference of the genders of the men and the women, so that the prediction result is more accurate.
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