Key result
Machine learning and data science promise to transform cardiovascular health via personalized care and early detection.
Why the study?
The study aims to highlight how data science, predictive modeling, and machine learning can transform healthcare systems, deliver customized cardiac care, and empower individuals to manage their cardiovascular health.
Data science, including predictive modeling and machine learning, has the potential to transform customized cardiac care and resource allocation while requiring strict adherence to ethical and privacy standards.
An analysis of how data science and healthcare are developing together indicated new possibilities to improve daily life and medical services, especially with regard to heart health. In order to provide customized cardiac care and resource allocation, it analyzes how technologies such as predictive modeling, analytics, and machine learning will change healthcare systems. It emphasizes the importance of maintaining ethical standards, security, and privacy, as well as appropriately handling cardiac health data. It highlights the revolutionary power of data science through real-life examples of enhancing patient care, supporting community health programs, and bringing about beneficial changes across the healthcare industry. The ultimate objective is to highlight the significance that data analytics can play in helping people to take control of their cardiovascular health and take well-informed choices about the treatment of their diseases.
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Prakalya et al. (2024) conducted a review in Cardiovascular disease. Data science and analytics was evaluated. Data science, predictive modeling, and machine learning offer transformative potential for cardiovascular health by enabling personalized care, early disease detection, and optimized resource allocation.
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