Cited by 347Artificial Intelligence in Healthcare and EducationArtificial Intelligence in HealthcareMachine Learning in Healthcare

Use of artificial intelligence in improving outcomes in heart disease: a scientific statement from the American Heart Association

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Armoundas, Antonis A., Narayan, Sanjiv M., Arnett, Donna K., Spector-Bagdady, Kayte, Bennett, Derrick A., Celi, Leo Anthony, Friedman, Paul A., Gollob, Michael H. +7 more·2024·Circulation

Abstract

A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.

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  1. [76]ALIVECOR. FDA clears personal ECG device for measurement of QTc interval, a critical marker for patient safety. July 8, 2021. https://www.Alivecor.Com/press/press_release/fda-clears-personal-ecg-device-for-measurement-of-qtc-interval/
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Authors
Armoundas, A. A., Narayan, S. M., Arnett, D. K., Spector-Bagdady, K., Bennett, D. A., Celi, L. A., Friedman, P. A., Gollob, M. H., Hall, J. L., Kwitek, A. E., Lett, E., Menon, B. K., Sheehan, K. A., Al-Zaiti, S. S., & on behalf of the American Heart Association Institute for Precision Cardiovascular Medicine; Council on Cardiovascular and Stroke Nursing; Council on Lifelong Congenital Heart Disease and Heart Health in the Young; Council on Cardiovascular Radiology and Intervention; Council on Hypertension; Council on the Kidney in Cardiovascular Disease; and Stroke Council
Venue
Circulation
Published
2024-04-02
Volume
149
Issue
14
Pages
e1028-e1050
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
OpenAlex
W4392238077
Cited by
347
References
181
Citations by year
2026: 181 · 2025: 137 · 2024: 28 · 2022: 1
FWCI
7.89
Type
journal article
Language
en
Open access
Locations
  • Circulation (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Heart, Lung, and Blood Institute (R01HL083359, R01HL149134, R01HL162260, R01HL064541)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Keywords
artificial intelligence, cardiovascular disease, stroke, precision medicine, diagnosis, disease classification, treatment, digital health tools, algorithmic bias, clinical teaching, implementation science, cardiovascular outcomes
MeSH terms
American Heart Association, Artificial Intelligence, Cardiovascular Diseases, Heart Diseases, Humans, United States, Stroke

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