Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review
Data science is likely to lead to major changes in cardiovascular imaging. Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of artificial intelligence (AI) is dependent on robust data; the application of appropriate computational approa...
| Main Authors: | , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2019
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| _version_ | 1797101275604582400 |
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| author | Dey, D Slomka, P Leeson, C Comaniciu, D Shrestha, S Sengupta, P Marwick, T |
| author_facet | Dey, D Slomka, P Leeson, C Comaniciu, D Shrestha, S Sengupta, P Marwick, T |
| author_sort | Dey, D |
| collection | OXFORD |
| description | Data science is likely to lead to major changes in cardiovascular imaging. Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of artificial intelligence (AI) is dependent on robust data; the application of appropriate computational approaches and tools; and validation of its clinical application to image segmentation, automated measurements, and eventually, automated diagnosis. AI may reduce cost and improve value at the stages of image acquisition, interpretation, and decision-making. Moreover, the precision now possible with cardiovascular imaging, combined with "big data" from the electronic health record and pathology, is likely to better characterize disease and personalize therapy. This review summarizes recent promising applications of AI in cardiology and cardiac imaging, which potentially add value to patient care. |
| first_indexed | 2024-03-07T05:49:32Z |
| format | Journal article |
| id | oxford-uuid:e862aa9c-aab2-4260-9208-4f539bfa3bd3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:49:32Z |
| publishDate | 2019 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:e862aa9c-aab2-4260-9208-4f539bfa3bd32022-03-27T10:46:19ZArtificial intelligence in cardiovascular imaging: JACC state-of-the-art reviewJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e862aa9c-aab2-4260-9208-4f539bfa3bd3EnglishSymplectic Elements at OxfordElsevier2019Dey, DSlomka, PLeeson, CComaniciu, DShrestha, SSengupta, PMarwick, TData science is likely to lead to major changes in cardiovascular imaging. Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of artificial intelligence (AI) is dependent on robust data; the application of appropriate computational approaches and tools; and validation of its clinical application to image segmentation, automated measurements, and eventually, automated diagnosis. AI may reduce cost and improve value at the stages of image acquisition, interpretation, and decision-making. Moreover, the precision now possible with cardiovascular imaging, combined with "big data" from the electronic health record and pathology, is likely to better characterize disease and personalize therapy. This review summarizes recent promising applications of AI in cardiology and cardiac imaging, which potentially add value to patient care. |
| spellingShingle | Dey, D Slomka, P Leeson, C Comaniciu, D Shrestha, S Sengupta, P Marwick, T Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review |
| title | Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review |
| title_full | Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review |
| title_fullStr | Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review |
| title_full_unstemmed | Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review |
| title_short | Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review |
| title_sort | artificial intelligence in cardiovascular imaging jacc state of the art review |
| work_keys_str_mv | AT deyd artificialintelligenceincardiovascularimagingjaccstateoftheartreview AT slomkap artificialintelligenceincardiovascularimagingjaccstateoftheartreview AT leesonc artificialintelligenceincardiovascularimagingjaccstateoftheartreview AT comaniciud artificialintelligenceincardiovascularimagingjaccstateoftheartreview AT shresthas artificialintelligenceincardiovascularimagingjaccstateoftheartreview AT senguptap artificialintelligenceincardiovascularimagingjaccstateoftheartreview AT marwickt artificialintelligenceincardiovascularimagingjaccstateoftheartreview |