Automation, machine learning, and artificial intelligence in echocardiography: A brave new world
- PMID: 29974498
- DOI: 10.1111/echo.14086
Automation, machine learning, and artificial intelligence in echocardiography: A brave new world
Abstract
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to improve accuracy and efficiency of manual tracings. Automation with longitudinal strain and 3D echocardiography has shown great accuracy and reproducibility allowing the incorporation of these techniques into daily workflow. This will give further experience to nonexpert readers and allow the integration of these essential tools into more echocardiography laboratories. The potential for machine learning in cardiovascular imaging is still being discovered as algorithms are being created, with training on large data sets beyond what traditional statistical reasoning can handle. Deep learning when applied to large image repositories will recognize complex relationships and patterns integrating all properties of the image, which will unlock further connections about the natural history and prognosis of cardiac disease states. The purpose of this review article was to describe the role and current use of automation, machine learning, and AI in echocardiography and discuss potential limitations and challenges of in the future.
Keywords: algorithm; artificial intelligence; automation; deep learning; echocardiography; machine learning.
© 2018 Wiley Periodicals, Inc.
Similar articles
-
Applications of artificial intelligence and machine learning approaches in echocardiography.Echocardiography. 2021 Jun;38(6):982-992. doi: 10.1111/echo.15048. Epub 2021 May 13. Echocardiography. 2021. PMID: 33982820 Review.
-
Machine Learning Approaches in Cardiovascular Imaging.Circ Cardiovasc Imaging. 2017 Oct;10(10):e005614. doi: 10.1161/CIRCIMAGING.117.005614. Circ Cardiovasc Imaging. 2017. PMID: 28956772 Free PMC article. Review.
-
Utilization of Artificial Intelligence in Echocardiography.Circ J. 2019 Jul 25;83(8):1623-1629. doi: 10.1253/circj.CJ-19-0420. Epub 2019 Jun 29. Circ J. 2019. PMID: 31257314 Review.
-
Automated Quantification in Echocardiography.JACC Cardiovasc Imaging. 2019 Jun;12(6):1073-1092. doi: 10.1016/j.jcmg.2018.11.038. JACC Cardiovasc Imaging. 2019. PMID: 31171260 Review.
-
The Role of Artificial Intelligence and Machine Learning in Clinical Cardiac Electrophysiology.Can J Cardiol. 2022 Feb;38(2):246-258. doi: 10.1016/j.cjca.2021.07.016. Epub 2021 Jul 29. Can J Cardiol. 2022. PMID: 34333029 Review.
Cited by
-
Microbiome-Driven Proline Biogenesis in Plants under Stress: Perspectives for Balanced Diet to Minimize Depression Disorders in Humans.Microorganisms. 2022 Nov 15;10(11):2264. doi: 10.3390/microorganisms10112264. Microorganisms. 2022. PMID: 36422335 Free PMC article. Review.
-
The application of convolutional neural network to stem cell biology.Inflamm Regen. 2019 Jul 5;39:14. doi: 10.1186/s41232-019-0103-3. eCollection 2019. Inflamm Regen. 2019. PMID: 31312276 Free PMC article. Review.
-
Diagnostic Accuracy of Machine Learning Models to Identify Congenital Heart Disease: A Meta-Analysis.Front Artif Intell. 2021 Jul 8;4:708365. doi: 10.3389/frai.2021.708365. eCollection 2021. Front Artif Intell. 2021. PMID: 34308341 Free PMC article. Review.
-
Deep learning from latent spatiotemporal information of the heart: Identifying advanced bioimaging markers from echocardiograms.Biophys Rev (Melville). 2024 Mar 27;5(1):011304. doi: 10.1063/5.0176850. eCollection 2024 Mar. Biophys Rev (Melville). 2024. PMID: 38559589 Free PMC article. Review.
-
Advanced Echocardiography Techniques: The Future Stethoscope of Systemic Diseases.Curr Probl Cardiol. 2022 Jun;47(6):100847. doi: 10.1016/j.cpcardiol.2021.100847. Epub 2021 Mar 30. Curr Probl Cardiol. 2022. PMID: 33992429 Free PMC article. Review.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical