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Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges
BACKGROUND: Numerous artificial intelligence (AI)-enabled tools for cardiovascular diseases have been published, with a high impact on public health. However, few have been adopted into, or have meaningfully affected, routine clinical care. OBJECTIVE: To evaluate current awareness, perceptions, and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10282011/ https://www.ncbi.nlm.nih.gov/pubmed/37351333 http://dx.doi.org/10.1016/j.cvdhj.2023.04.003 |
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author | Schepart, Alexander Burton, Arianna Durkin, Larry Fuller, Allison Charap, Ellyn Bhambri, Rahul Ahmad, Faraz S. |
author_facet | Schepart, Alexander Burton, Arianna Durkin, Larry Fuller, Allison Charap, Ellyn Bhambri, Rahul Ahmad, Faraz S. |
author_sort | Schepart, Alexander |
collection | PubMed |
description | BACKGROUND: Numerous artificial intelligence (AI)-enabled tools for cardiovascular diseases have been published, with a high impact on public health. However, few have been adopted into, or have meaningfully affected, routine clinical care. OBJECTIVE: To evaluate current awareness, perceptions, and clinical use of AI-enabled digital health tools for patients with cardiovascular disease, and challenges to adoption. METHODS: This mixed-methods study included interviews with 12 cardiologists and 8 health information technology (IT) administrators, and a follow-on survey of 90 cardiologists and 30 IT administrators. RESULTS: We identified 5 major challenges: (1) limited knowledge, (2) insufficient usability, (3) cost constraints, (4) poor electronic health record interoperability, and (5) lack of trust. A minority of cardiologists were using AI tools; more were prepared to implement AI tools, but their sophistication level varied greatly. CONCLUSION: Most respondents believe in the potential of AI-enabled tools to improve care quality and efficiency, but they identified several fundamental barriers to wide-scale adoption. |
format | Online Article Text |
id | pubmed-10282011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102820112023-06-22 Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges Schepart, Alexander Burton, Arianna Durkin, Larry Fuller, Allison Charap, Ellyn Bhambri, Rahul Ahmad, Faraz S. Cardiovasc Digit Health J Original Article BACKGROUND: Numerous artificial intelligence (AI)-enabled tools for cardiovascular diseases have been published, with a high impact on public health. However, few have been adopted into, or have meaningfully affected, routine clinical care. OBJECTIVE: To evaluate current awareness, perceptions, and clinical use of AI-enabled digital health tools for patients with cardiovascular disease, and challenges to adoption. METHODS: This mixed-methods study included interviews with 12 cardiologists and 8 health information technology (IT) administrators, and a follow-on survey of 90 cardiologists and 30 IT administrators. RESULTS: We identified 5 major challenges: (1) limited knowledge, (2) insufficient usability, (3) cost constraints, (4) poor electronic health record interoperability, and (5) lack of trust. A minority of cardiologists were using AI tools; more were prepared to implement AI tools, but their sophistication level varied greatly. CONCLUSION: Most respondents believe in the potential of AI-enabled tools to improve care quality and efficiency, but they identified several fundamental barriers to wide-scale adoption. Elsevier 2023-05-03 /pmc/articles/PMC10282011/ /pubmed/37351333 http://dx.doi.org/10.1016/j.cvdhj.2023.04.003 Text en © 2023 Heart Rhythm Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Schepart, Alexander Burton, Arianna Durkin, Larry Fuller, Allison Charap, Ellyn Bhambri, Rahul Ahmad, Faraz S. Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges |
title | Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges |
title_full | Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges |
title_fullStr | Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges |
title_full_unstemmed | Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges |
title_short | Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges |
title_sort | artificial intelligence–enabled tools in cardiovascular medicine: a survey of current use, perceptions, and challenges |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10282011/ https://www.ncbi.nlm.nih.gov/pubmed/37351333 http://dx.doi.org/10.1016/j.cvdhj.2023.04.003 |
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