ISSN: 2582 - 9734
A Review Study on Heart Disease Prediction System using ML Algorithms
Deepak Upadhyay, Ankit Garg
CrossRef DOI URL : https://doi.org/10.31426/ijesti.2023.3.11.3911
The fact that cardiovascular disease is the leading cause of mortality throughout the whole world poses significant challenges for the organisations that are accountable for the health of the general people. Early detection and accurate prediction can substantially improve patient outcomes and reduce healthcare costs. Traditional diagnostic methods, while effective, often involve invasive procedures or subjective interpretations, highlighting the need for more efficient solutions. Integrating machine learning algorithms into healthcare has shown promise in enhancing diagnostic accuracy and predictive capabilities. The field of machine learning is able to effectively examine massive datasets, detect patterns, and generate predictions thanks to the use of computer models. With the use of advanced machine learning techniques, the objective of this study is to develop a one-of-a-kind system that can accurately forecast cardiac sickness. Support vector machines, neural networks, and decision trees are some of the methods that fall under this category. The objective of this attempt is to create a predictive model that not only improves the accuracy of identifying cardiac illness but also easily integrates into the healthcare systems that are currently in place. This will be accomplished without any difficulties. This research addresses gaps in heart disease prediction by offering more accurate, efficient, and user-friendly solutions, potentially leading to better health management practices and improved patient outcomes..
2024
30
