Back to Search
Start Over
Advances in Diagnosis, Therapy, and Prognosis of Coronary Artery Disease Powered by Deep Learning Algorithms.
- Source :
-
JACC. Asia [JACC Asia] 2023 Feb 15; Vol. 3 (1), pp. 1-14. Date of Electronic Publication: 2023 Feb 15 (Print Publication: 2023). - Publication Year :
- 2023
-
Abstract
- Percutaneous coronary intervention has been a standard treatment strategy for patients with coronary artery disease with continuous ebullient progress in technology and techniques. The application of artificial intelligence and deep learning in particular is currently boosting the development of interventional solutions, improving the efficiency and objectivity of diagnosis and treatment. The ever-growing amount of data and computing power together with cutting-edge algorithms pave the way for the integration of deep learning into clinical practice, which has revolutionized the interventional workflow in imaging processing, interpretation, and navigation. This review discusses the development of deep learning algorithms and their corresponding evaluation metrics together with their clinical applications. Advanced deep learning algorithms create new opportunities for precise diagnosis and tailored treatment with a high degree of automation, reduced radiation, and enhanced risk stratification. Generalization, interpretability, and regulatory issues are remaining challenges that need to be addressed through joint efforts from multidisciplinary community.<br />Competing Interests: This study was supported by the Natural Science Foundation of China (82020108015 and 81871460). Dr Tu reported research grants and consultancy from Pulse Medical. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.<br /> (© 2023 The Authors.)
Details
- Language :
- English
- ISSN :
- 2772-3747
- Volume :
- 3
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- JACC. Asia
- Publication Type :
- Academic Journal
- Accession number :
- 36873752
- Full Text :
- https://doi.org/10.1016/j.jacasi.2022.12.005