Predictive Modeling and Personalized Care: MachineLearning's Impact on Cardiovascular Disease (CVD) Prevention
Abstract
Global burden of cardiovascular disease (CVD) accounts for high mortality and developing new intervention strategies for early detection, risk assessment, and individualized management. Machine learning is a revolutionary technology in healthcare and is capable to discover new patterns from complex datasets in large amount than other traditional approaches. Continuing this article, the subject area is going to be defined in what extent machine learning supports the prevention of CVD through the application of predictive modeling, personalized treatments and constant supervision and monitoring. With the help of ML algorithms, clinicians will be able to forecast cardiovascular events, individualize patient care treatment, and track a patient’s state with the help of wearable devices. The introduction of ML in clinical practice enhances both the probabilities of risk assessment and provides better strategies of prevention compared to the conventional methods, hence a giant stride on the fight against CVD.
Keywords
Cardiovascular disease prevention, Machine learning, Predictive modeling, risk stratification, personalized treatment, Healthcare technology, Artificial intelligence, Wearable health monitoring, Predictive analytics.
Citations
IRE Journals:
Anshul Khairari , Priyabrata Thatoi , Sushree Swapnil Rout , Pooja Patil
"Predictive Modeling and Personalized Care: MachineLearning's Impact on Cardiovascular Disease (CVD) Prevention" Iconic Research And Engineering Journals Volume 7 Issue 2 2023 Page 683-689
IEEE:
Anshul Khairari , Priyabrata Thatoi , Sushree Swapnil Rout , Pooja Patil
"Predictive Modeling and Personalized Care: MachineLearning's Impact on Cardiovascular Disease (CVD) Prevention" Iconic Research And Engineering Journals, 7(2)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
Important Links
For Authors
Volume 7:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 6:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 5:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 4:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 3:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12