Predicting Cardiovascular Aging Risk Based on Clinical Data Through the Integration of Mathematical Modeling and Machine Learning

Predicting Cardiovascular Aging Risk Based on Clinical Data Through the Integration of Mathematical Modeling and Machine Learning

Background: The aging population is increasing rapidly, with individuals aged 65 and older now representing more than 15% of the global population. This demographic shift is associated with a rising incidence of age-related cardiovascular diseases (CVDs). Early prediction and prevention of cardiovas...

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Main Authors: Kuat Abzaliyev, Madina Suleimenova, Siming Chen, Madina Mansurova, Symbat Abzaliyeva, Ainur Manapova, Almagul Kurmanova, Akbota Bugibayeva, Diana Sundetova, Raushan Bitemirova, Nazipa Baizhigitova, Merey Abdykassymova, Ulzhas Sagalbayeva
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
cardiovascular aging
prediction
mathematical modelling
elderly patients
physiological factors
differential equations
Online Access:https://www.mdpi.com/2076-3417/15/9/5077
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