Optimizing Stent Placement in Coronary Artery: The Role of Artificial Intelligence in Improving Patient Outcomes

Research Article


Abstract views: 96 / PDF downloads: 49

Authors

  • N John Camm

DOI:

https://doi.org/10.58372/2835-6276.1025

Keywords:

AI, Cardiovascular Disease, Coronary Angioplast, Stenting, Machine learning

Abstract

Artificial Intelligence (AI) has the potential to revolutionize the way coronary angioplasty is performed by providing real-time analysis and guidance during the procedure. Stent placement is a critical aspect of coronary angioplasty and optimizing the placement of stents can lead to improved patient outcomes. AI algorithms can simulate different stent placement scenarios and identify the best one that minimizes the risk of restenosis and improves blood flow. AI-powered tools can assist interventional cardiologists in determining the optimal stent placement location, guiding them towards precise stent deployment, and reducing the risk of adverse events. This abstract aims to provide an overview of the role of AI in optimizing stent placement during coronary angioplasty and the potential benefits it offers in terms of improved patient outcomes. The use of AI in this field is still in its early stages, and future advancements are expected to further improve its efficacy and impact on patient outcomes.The use of AI in coronary angioplasty has the potential to improve patient outcomes by reducing the risk of adverse events and restenosis. AI algorithms can analyze angiographic images of the coronary arteries in real-time and provide information on the best stent placement location and deployment strategy for each individual patient. This information can help interventional cardiologists to make informed decisions and improve the precision of stent deployment. Additionally, AI algorithms can be used for predictive modeling and risk assessment, enabling interventional cardiologists to make decisions that are tailored to each patient's unique needs and circumstances.The future of AI in coronary angioplasty is bright, and many exciting advancements are expected in the near future. AI algorithms will continue to evolve and become more sophisticated, providing interventional cardiologists with even more precise guidance and information during the procedure. Additionally, AI-powered tools for stent design and deployment are likely to be developed, leading to improved stent deployment, reduced restenosis rates, and improved patient outcomes.The role of AI in optimizing stent placement during coronary angioplasty is becoming increasingly important, and its potential benefits are numerous. This article review the potential to revolutionize the field of interventional cardiology and improve patient outcomes, and its use is expected to continue to grow in the years to come.

References

Choudhury, A. K., Ali, Z., & Al-Lamee, R. (2020). Artificial intelligence in interventional cardiology: state of the art. Journal of the Royal Society of Medicine, 113(3), 78-85.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Choudhury, A. K., Ali, Z., & Al-Lamee, R. (2020). Artificial intelligence in interventional cardiology: state of the art. Journal of the Royal Society of Medicine, 113(3), 78-85.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Choudhury, A. K., Ali, Z., & Al-Lamee, R. (2020). Artificial intelligence in interventional cardiology: state of the art. Journal of the Royal Society of Medicine, 113(3), 78-85.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Choudhury, A. K., Ali, Z., & Al-Lamee, R. (2020). Artificial intelligence in interventional cardiology: state of the art. Journal of the Royal Society of Medicine, 113(3), 78-85.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Choudhury, A. K., Ali, Z., & Al-Lamee, R. (2020). Artificial intelligence in interventional cardiology: state of the art. Journal of the Royal Society of Medicine, 113(3), 78-85.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Choudhury, A. K., Ali, Z., & Al-Lamee, R. (2020). Artificial intelligence in interventional cardiology: state of the art. Journal of the Royal Society of Medicine, 113(3), 78-85.

Furnary, A. P., Zocchi, M., & Wu, J. (2020). Artificial intelligence in interventional cardiology. Circulation research, 126(7), 905-917.

Downloads

Published

2023-02-17

How to Cite

N John Camm. (2023). Optimizing Stent Placement in Coronary Artery: The Role of Artificial Intelligence in Improving Patient Outcomes: Research Article. American Journal of Medical and Clinical Research & Reviews, 2(2), 1–7. https://doi.org/10.58372/2835-6276.1025

Issue

Section

Articles