Optimizing Real-Time Data Analytics in Healthcare: A Predictive Model for Cardiovascular Disease Management

Yeruva, Venkata Krishna Reddy (2025) Optimizing Real-Time Data Analytics in Healthcare: A Predictive Model for Cardiovascular Disease Management. Masters thesis, Dublin, National College of Ireland.

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Abstract

Cardiovascular disease continues to be a global leading cause of death, but conventional prediction techniques often lack the ability for real-time and customized intervention. The paper proposes solving the problem of predictive accuracy by using machine learning algorithms for the prediction of cardiovascular disease based on lifestyle and clinical information. The research made use of the Kaggle Cardiovascular Disease dataset containing 70,000 patients. The initial preprocessing involved the removal of outliers and scaling of features. Feature selection using SHAP values and RFECV followed. Three supervised learning classifiers—Decision Tree, Random Forest, and Support Vector Machine (SVM)—were created and tested. The SVM model returned the best accuracy of 72%. It was also found through statistical analysis that cardiovascular disease had strong correlation with lifestyle habits like smoking and inactivity. The study illustrates how machine learning could be used for early detection and customized healthcare planning and explains its importance for preventive interventions in the future.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Qayum, Abdul UNSPECIFIED
Uncontrolled Keywords:	Cardiovascular Disease; Machine Learning; SHAP; Feature Selection; Support Vector Machine; Predictive Modeling; Statistical Analysis; Healthcare AI
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence R Medicine > Healthcare Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	18 Nov 2025 17:59
Last Modified:	18 Nov 2025 17:59
URI:	https://norma.ncirl.ie/id/eprint/8946

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