Citation

Khan, M. Reyasudin Basir and Islam, Gazi Md. Nurul and Ng, Poh Kiat and Zainuddin, Ahmad Anwar and Lean, Chong Peng and Al-Fattah, Jabbar and Kamarudin, Saidatul Izyanie (2024) Empowering decision-making in cardiovascular care: Exploratory data analysis and predictive models for heart attack risk. In: 6th ISM International Statistical Conference, ISM 2023, 19-20 September 2023, Shah Alam, Malaysia.

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Abstract

Acute myocardial infarction, commonly referred to as a heart attack, stands as one of the most lethal medical conditions, highlighting the pressing necessity for the effective management of cardiovascular disease. This involves conducting comprehensive data analysis and extracting knowledge essential for diagnosis, regulation, and treatment. Anticipating the occurrence of heart attacks presents a formidable challenge for healthcare professionals, given the intricate nature of the condition that demands both experience and a profound understanding. In the contemporary landscape of medicine, the concealed data landscape conceals invaluable insights that can significantly shape critical decision-making processes. In this research endeavor, a dataset comprising patient records is harnessed to predict an individual’s vulnerability to heart attacks. Advanced data visualization techniques are employed to identify pivotal trends and outliers, facilitating the extraction of meaningful and actionable conclusions. This study involves the development of three classifier models for heart attack prediction: Logistic Regression, K Nearest Neighbor, and Support Vector model.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	cardiovascular, health care
Subjects:	R Medicine > RC Internal medicine > RC71-78.7 Examination. Diagnosis
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Oct 2024 00:48
Last Modified:	01 Oct 2024 00:48
URII:	http://shdl.mmu.edu.my/id/eprint/12990

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