Artificial Intelligence in Nuclear Cardiology

Robert J H Miller

doi:10.1016/j.ccl.2023.01.004

Artificial Intelligence in Nuclear Cardiology

Cardiol Clin. 2023 May;41(2):151-161. doi: 10.1016/j.ccl.2023.01.004. Epub 2023 Feb 20.

Author

Robert J H Miller¹

Affiliation

¹ Department of Cardiac Sciences, University of Calgary, GAA08, 3230 Hospital Drive Northwest, Calgary, Alberta T2N 2T9, Canada. Electronic address: robert.miller@albertahealthservices.ca.

PMID: 37003673
DOI: 10.1016/j.ccl.2023.01.004

Abstract

Artificial intelligence (AI) encompasses a variety of computer algorithms that have a wide range of potential clinical applications in nuclear cardiology. This article will introduce core terminology and concepts for AI including classifications of AI as well as training and testing regimens. We will then highlight the potential role for AI to improve image registration and image quality. Next, we will discuss methods for AI-driven image attenuation correction. Finally, we will review advancements in machine learning and deep-learning applications for disease diagnosis and risk stratification, including efforts to improve clinical translation of this valuable technology with explainable AI models.

Keywords: Artificial intelligence; Deep learning; Machine learning; Nuclear cardiology.

Publication types

Review

MeSH terms

Algorithms
Artificial Intelligence
Cardiology* / methods
Deep Learning*
Humans
Machine Learning