TY - JOUR
T1 - Current and Future Applications of Artificial Intelligence in Coronary Artery Disease
AU - Gautam, Nitesh
AU - Saluja, Prachi
AU - Malkawi, Abdallah
AU - Rabbat, Mark G.
AU - Al-Mallah, Mouaz H.
AU - Pontone, Gianluca
AU - Zhang, Yiye
AU - Lee, Benjamin C.
AU - Al’Aref, Subhi J.
N1 - Funding Information:
Conflicts of Interest: Subhi J. Al’Aref is supported by NIH 2R01 HL12766105 & 1R21 EB030654 and receives royalty fees from Elsevier. Gianluca Pontone receives honorarium and institutional research funding from GE Healthcare, Bracco, Boehringer Ingelheim, Bayer, and Heartflow. Mouaz Al-Mallah receives research support from SiEMENS and consulting fee/honorarium from Philips, Pfizer, and Draximage. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/2
Y1 - 2022/2
N2 - Cardiovascular diseases (CVDs) carry significant morbidity and mortality and are associated with substantial economic burden on healthcare systems around the world. Coronary artery disease, as one disease entity under the CVDs umbrella, had a prevalence of 7.2% among adults in the United States and incurred a financial burden of 360 billion US dollars in the years 2016–2017. The introduction of artificial intelligence (AI) and machine learning over the last two decades has unlocked new dimensions in the field of cardiovascular medicine. From automatic interpretations of heart rhythm disorders via smartwatches, to assisting in complex decision-making, AI has quickly expanded its realms in medicine and has demonstrated itself as a promising tool in helping clinicians guide treatment decisions. Understanding complex genetic interactions and developing clinical risk prediction models, advanced cardiac imaging, and improving mortality outcomes are just a few areas where AI has been applied in the domain of coronary artery disease. Through this review, we sought to summarize the advances in AI relating to coronary artery disease, current limitations, and future perspectives.
AB - Cardiovascular diseases (CVDs) carry significant morbidity and mortality and are associated with substantial economic burden on healthcare systems around the world. Coronary artery disease, as one disease entity under the CVDs umbrella, had a prevalence of 7.2% among adults in the United States and incurred a financial burden of 360 billion US dollars in the years 2016–2017. The introduction of artificial intelligence (AI) and machine learning over the last two decades has unlocked new dimensions in the field of cardiovascular medicine. From automatic interpretations of heart rhythm disorders via smartwatches, to assisting in complex decision-making, AI has quickly expanded its realms in medicine and has demonstrated itself as a promising tool in helping clinicians guide treatment decisions. Understanding complex genetic interactions and developing clinical risk prediction models, advanced cardiac imaging, and improving mortality outcomes are just a few areas where AI has been applied in the domain of coronary artery disease. Through this review, we sought to summarize the advances in AI relating to coronary artery disease, current limitations, and future perspectives.
KW - Artificial intelligence
KW - Cardiac computed tomography
KW - Coronary artery disease
KW - Fractional flow reserve
KW - Major adverse cardiovascular events
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U2 - 10.3390/healthcare10020232
DO - 10.3390/healthcare10020232
M3 - Review article
AN - SCOPUS:85123553815
VL - 10
JO - Healthcare (Switzerland)
JF - Healthcare (Switzerland)
SN - 2227-9032
IS - 2
M1 - 232
ER -