Artificial Intelligence in Cardiology: Present and Future
Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search term...
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| Published in: | Mayo Clinic proceedings Vol. 95; no. 5; pp. 1015 - 1039 |
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| Main Authors: | , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Elsevier Inc
01.05.2020
Frontline Medical Communications Inc Elsevier Limited |
| Subjects: | |
| ISSN: | 0025-6196, 1942-5546, 1942-5546 |
| Online Access: | Get full text |
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| Abstract | Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel. |
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| AbstractList | Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel. Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel.Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel. |
| Audience | Academic |
| Author | Friedman, Paul A. Senecal, Conor Attia, Zachi Jouni, Hayan Arruda-Olson, Adelaide M. Luong, Christina Carter, Rickey Roger, Veronique L. Lerman, Amir Kapa, Suraj Lopez-Jimenez, Francisco Chareonthaitawee, Panithaya Noseworthy, Peter A. Medina-Inojosa, Jose R. Pellikka, Patricia A. Redfield, Margaret M. Sandhu, Gurpreet S. |
| Author_xml | – sequence: 1 givenname: Francisco orcidid: 0000-0001-5788-9734 surname: Lopez-Jimenez fullname: Lopez-Jimenez, Francisco email: lopez@mayo.edu organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 2 givenname: Zachi surname: Attia fullname: Attia, Zachi organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 3 givenname: Adelaide M. orcidid: 0000-0001-9541-9899 surname: Arruda-Olson fullname: Arruda-Olson, Adelaide M. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 4 givenname: Rickey orcidid: 0000-0002-0818-273X surname: Carter fullname: Carter, Rickey organization: Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL – sequence: 5 givenname: Panithaya surname: Chareonthaitawee fullname: Chareonthaitawee, Panithaya organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 6 givenname: Hayan surname: Jouni fullname: Jouni, Hayan organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 7 givenname: Suraj surname: Kapa fullname: Kapa, Suraj organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 8 givenname: Amir orcidid: 0000-0002-9446-5313 surname: Lerman fullname: Lerman, Amir organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 9 givenname: Christina surname: Luong fullname: Luong, Christina organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 10 givenname: Jose R. orcidid: 0000-0001-8705-0462 surname: Medina-Inojosa fullname: Medina-Inojosa, Jose R. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 11 givenname: Peter A. surname: Noseworthy fullname: Noseworthy, Peter A. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 12 givenname: Patricia A. orcidid: 0000-0001-6800-3521 surname: Pellikka fullname: Pellikka, Patricia A. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 13 givenname: Margaret M. surname: Redfield fullname: Redfield, Margaret M. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 14 givenname: Veronique L. orcidid: 0000-0002-9347-7865 surname: Roger fullname: Roger, Veronique L. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 15 givenname: Gurpreet S. surname: Sandhu fullname: Sandhu, Gurpreet S. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 16 givenname: Conor surname: Senecal fullname: Senecal, Conor organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN – sequence: 17 givenname: Paul A. orcidid: 0000-0001-5052-2948 surname: Friedman fullname: Friedman, Paul A. organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32370835$$D View this record in MEDLINE/PubMed |
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| Copyright | 2020 Mayo Foundation for Medical Education and Research Copyright © 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved. COPYRIGHT 2020 Frontline Medical Communications Inc. Copyright Mayo Foundation for Medical Education and Research May 2020 |
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