The research of influence factors that possibly lead to cardiovascular disease

Abstract

Abstract. The emergence of cardiac disease is influenced by numerous variables. Every year a large percentage of people around the world die from heart attacks. This study was to look at how important clinical variables are connected to the chance of having CVD. The analysis used a Kaggle dataset with details from 70,000 patients and 10 different variables. The study examined how factors such as age, gender and changes in cardiac activity during exercise affect overall heart health. Multiple linear regression models were used to analyze these effects. The results show a significant correlation between these factors and an increased risk of heart disease. This emphasizes the importance of these predictors in clinical assessments. It can be concluded from this study that regular medical check-ups, early prevention and treatment should be carried out for these vulnerable groups. The general prevalence of heart disease in the nation can be decreased by implementing these strategies. According to the study, personalized health strategies have the potential to improve CVD outcomes and strengthen preventive measures. All of the experimental results suggest that continued documentation and study of these pathogenic factors in medical diagnostics and experiments could aid in drug development as well as improve medical technology and help more patients with cardiovascular disease recover.