Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects
Ikram U Haq,1 Karanjot Chhatwal,2 Krishna Sanaka,3 Bo Xu4 1Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55905, USA; 2Imperial College London School of Medicine, London, SW7 2AZ, UK; 3Emory University, Atlanta, GA, 30322, USA; 4Section of Cardiovascular Imaging, Robert and Suzanne Tom...
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| Format: | Article |
| Language: | English |
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Dove Medical Press
2022-07-01
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| Series: | Vascular Health and Risk Management |
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| Online Access: | https://www.dovepress.com/artificial-intelligence-in-cardiovascular-medicine-current-insights-an-peer-reviewed-fulltext-article-VHRM |
| _version_ | 1811297063589117952 |
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| author | Haq IU Chhatwal K Sanaka K Xu B |
| author_facet | Haq IU Chhatwal K Sanaka K Xu B |
| author_sort | Haq IU |
| collection | DOAJ |
| description | Ikram U Haq,1 Karanjot Chhatwal,2 Krishna Sanaka,3 Bo Xu4 1Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55905, USA; 2Imperial College London School of Medicine, London, SW7 2AZ, UK; 3Emory University, Atlanta, GA, 30322, USA; 4Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, 44195, USACorrespondence: Bo Xu, Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Desk J1-5, Cleveland, OH, 44195, USA, Tel +1 216 444-2200, Fax +1 216 445-6152, Email xub@ccf.orgAbstract: Cardiovascular disease (CVD) represents a significant and increasing burden on healthcare systems. Artificial intelligence (AI) is a rapidly evolving transdisciplinary field employing machine learning (ML) techniques, which aim to simulate human intuition to offer cost-effective and scalable solutions to better manage CVD. ML algorithms are increasingly being developed and applied in various facets of cardiovascular medicine, including and not limited to heart failure, electrophysiology, valvular heart disease and coronary artery disease. Within heart failure, AI algorithms can augment diagnostic capabilities and clinical decision-making through automated cardiac measurements. Occult cardiac disease is increasingly being identified using ML from diagnostic data. Improved diagnostic and prognostic capabilities using ML algorithms are enhancing clinical care of patients with valvular heart disease and coronary artery disease. The growth of AI techniques is not without inherent challenges, most important of which is the need for greater external validation through multicenter, prospective clinical trials.Keywords: artificial intelligence, cardiovascular medicine, machine learning, neural networks |
| first_indexed | 2024-04-13T05:57:44Z |
| format | Article |
| id | doaj.art-4ddb52fe3df64eeb8ab737597f84599a |
| institution | Directory Open Access Journal |
| issn | 1178-2048 |
| language | English |
| last_indexed | 2024-04-13T05:57:44Z |
| publishDate | 2022-07-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | Vascular Health and Risk Management |
| spelling | doaj.art-4ddb52fe3df64eeb8ab737597f84599a2022-12-22T02:59:33ZengDove Medical PressVascular Health and Risk Management1178-20482022-07-01Volume 1851752876515Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future ProspectsHaq IUChhatwal KSanaka KXu BIkram U Haq,1 Karanjot Chhatwal,2 Krishna Sanaka,3 Bo Xu4 1Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55905, USA; 2Imperial College London School of Medicine, London, SW7 2AZ, UK; 3Emory University, Atlanta, GA, 30322, USA; 4Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, 44195, USACorrespondence: Bo Xu, Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Desk J1-5, Cleveland, OH, 44195, USA, Tel +1 216 444-2200, Fax +1 216 445-6152, Email xub@ccf.orgAbstract: Cardiovascular disease (CVD) represents a significant and increasing burden on healthcare systems. Artificial intelligence (AI) is a rapidly evolving transdisciplinary field employing machine learning (ML) techniques, which aim to simulate human intuition to offer cost-effective and scalable solutions to better manage CVD. ML algorithms are increasingly being developed and applied in various facets of cardiovascular medicine, including and not limited to heart failure, electrophysiology, valvular heart disease and coronary artery disease. Within heart failure, AI algorithms can augment diagnostic capabilities and clinical decision-making through automated cardiac measurements. Occult cardiac disease is increasingly being identified using ML from diagnostic data. Improved diagnostic and prognostic capabilities using ML algorithms are enhancing clinical care of patients with valvular heart disease and coronary artery disease. The growth of AI techniques is not without inherent challenges, most important of which is the need for greater external validation through multicenter, prospective clinical trials.Keywords: artificial intelligence, cardiovascular medicine, machine learning, neural networkshttps://www.dovepress.com/artificial-intelligence-in-cardiovascular-medicine-current-insights-an-peer-reviewed-fulltext-article-VHRMartificial intelligencecardiovascular medicinemachine learningneural networks |
| spellingShingle | Haq IU Chhatwal K Sanaka K Xu B Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects Vascular Health and Risk Management artificial intelligence cardiovascular medicine machine learning neural networks |
| title | Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects |
| title_full | Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects |
| title_fullStr | Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects |
| title_full_unstemmed | Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects |
| title_short | Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects |
| title_sort | artificial intelligence in cardiovascular medicine current insights and future prospects |
| topic | artificial intelligence cardiovascular medicine machine learning neural networks |
| url | https://www.dovepress.com/artificial-intelligence-in-cardiovascular-medicine-current-insights-an-peer-reviewed-fulltext-article-VHRM |
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