Sneha R Kandi, Rohan Khera, Sanjay Rajagopalan, Ian J Neeland
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引用次数: 0
Abstract
Purpose of review: This review explores the role of artificial intelligence (AI) in visceral adipose tissue (VAT) and ectopic fat imaging. It aims to evaluate how AI may be used to enhance the efficiency and accuracy of cardiovascular disease (CVD) risk assessment. It addresses key questions regarding AI's capabilities in risk prediction, segmentation, and integration with large volume data for CVD risk assessment.
Recent findings: Recent studies demonstrate that AI, powered by deep learning models, significantly improve VAT and ectopic fat segmentation. AI can also be used to facilitate early detection of cardiometabolic risks and allows integration of imaging with clinical data for a more personalized approach to medicine. Emerging applications include AI-enabled telehealth and continuous monitoring through wearable technologies. AI is transforming VAT and ectopic fat imaging by enabling more precise, personalized, and scalable assessments of fat distribution and cardiovascular risk. While challenges remain, such as model interpretability, future research will likely focus on refining algorithms and expanding AI's clinical applications, potentially redefining obesity and CVD risk management.
期刊介绍:
The aim of this journal is to systematically provide expert views on current basic science and clinical advances in the field of atherosclerosis and highlight the most important developments likely to transform the field of cardiovascular prevention, diagnosis, and treatment.
We accomplish this aim by appointing major authorities to serve as Section Editors who select leading experts from around the world to provide definitive reviews on key topics and papers published in the past year. We also provide supplementary reviews and commentaries from well-known figures in the field. An Editorial Board of internationally diverse members suggests topics of special interest to their country/region and ensures that topics are current and include emerging research.