Artificial intelligence (AI) describes the use of computational techniques to mimic human intelligence. In healthcare, this typically involves large medical datasets being used to predict a diagnosis, identify new disease genotypes or phenotypes, or guide treatment strategies. Noninvasive imaging remains a cornerstone for the diagnosis, risk stratification, and management of patients with cardiovascular disease. AI can facilitate every stage of the imaging process, from acquisition and reconstruction, to segmentation, measurement, interpretation, and subsequent clinical pathways.
In this paper, we review state-of-the-art AI techniques and their current applications in cardiac imaging, and discuss the future role of AI as a precision medicine tool.
Cardiovascular medicine is primed for scalable AI applications which can interpret vast amounts of clinical and imaging data in greater depth than ever before. AI-augmented medical systems have the potential to improve workflow and provide reproducible and objective quantitative results which can inform clinical decisions. In the foreseeable future, AI may work in the background of cardiac image analysis software and routine clinical reporting, automatically collecting data and enabling real-time diagnosis and risk stratification.
Artificial intelligence is being increasingly used to analyze big data generated by cardiovascular imaging
Machine learning and deep learning algorithms can automate image acquisition and reconstruction, segmentation, measurement, and interpretation
Integration of clinical and imaging data using machine learning risk scores provides personalized outcome prediction, enabling the practice of precision cardiovascular medicine
Radiomics is an new field of image analysis which enables quantification of features indiscernible to the human eye
In the near future, artificial intelligence may function as a precision medicine tool which aids physicians in clinical decision making
Declaration of interest
The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.