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22 May 2023 Analysis and prediction of cardiovascular disease prevalence in middle-aged and elderly men based on machine learning
Lijia Liu, Wanyue Sun, Yiming Dou
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Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 126401G (2023) https://doi.org/10.1117/12.2673928
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China
Abstract
Cardiovascular disease has dominated fatality cause in recent decades, the most vulnerable group of which, is reported to be middle-aged and older men based on much clinical research. This article intends to investigate the underlying reasons for such a group's susceptibility through the combination of empirical evidence and data analysis by logistic regression. In conclusion, it turns out that unhealthy habits such as chronic smoking, unlimited drinking, and the pronounced lack of estrogen protection exacerbated by the aging effect are the crucial reasons why there are more middle-aged and older male patients than females. In the final section, some tailored precautionary measures have been provided functioning as the relief of the aging-heart burden.
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Lijia Liu, Wanyue Sun, and Yiming Dou "Analysis and prediction of cardiovascular disease prevalence in middle-aged and elderly men based on machine learning", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 126401G (22 May 2023); https://doi.org/10.1117/12.2673928
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KEYWORDS
Cardiovascular disorders
Heart
Machine learning
Blood pressure
Data modeling
Data analysis
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