{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["4(3)"],"submitter":["Schepart A"],"pubmed_abstract":["<h4>Background</h4>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.<h4>Objective</h4>To evaluate current awareness, perceptions, and clinical use of AI-enabled digital health tools for patients with cardiovascular disease, and challenges to adoption.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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."],"journal":["Cardiovascular digital health journal"],"pagination":["101-110"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10282011"],"repository":["biostudies-literature"],"pubmed_title":["Artificial intelligence-enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges."],"pmcid":["PMC10282011"],"pubmed_authors":["Schepart A","Burton A","Fuller A","Charap E","Bhambri R","Durkin L","Ahmad FS"],"additional_accession":[]},"is_claimable":false,"name":"Artificial intelligence-enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges.","description":"<h4>Background</h4>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.<h4>Objective</h4>To evaluate current awareness, perceptions, and clinical use of AI-enabled digital health tools for patients with cardiovascular disease, and challenges to adoption.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jun","modification":"2025-04-04T07:38:36.541Z","creation":"2025-04-04T07:38:36.541Z"},"accession":"S-EPMC10282011","cross_references":{"pubmed":["37351333"],"doi":["10.1016/j.cvdhj.2023.04.003"]}}