Risk assessment for heart failure using multiple linear regression model

Yifan Wang

doi:10.1117/12.2668989

24 March 2023 Risk assessment for heart failure using multiple linear regression model

Yifan Wang

Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126114V (2023) https://doi.org/10.1117/12.2668989
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom

Abstract

Heart failure has become a chronic disease. However, due to population ageing and growth, the overall number of patients who suffering from heart failure is still increasing. The high rates of sickness and mortality also have substantial personal, societal, and financial repercussions. Therefore, scientists have also begun to pay attention to the influence of heart failure on human life, then the prediction of heart failure becomes particularly important. This study predicts the factors that may affect heart failure by using multiple linear regression model. The analysis of the model leads to the conclusion that a flat ST_Slope, atypical angina, and heart failure have a significant linear association. Even although the selection of the sample and the sample size still have the space to further improve in the future, this study exhibits the significant role to predict heart failure and aid in both early detection and prevention of the condition.

Citation Download Citation

Yifan Wang "Risk assessment for heart failure using multiple linear regression model", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126114V (24 March 2023); https://doi.org/10.1117/12.2668989

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