{"title":"揭示人工智能在心脏保健中实施的促进因素和障碍：INSIGHT-AI法国研究的基本原理和设计，来自法国心脏病学会人工智能工作组和国家心脏病专家培训学院。","authors":"Antonin Trimaille, Stéphane Lafitte, Floran Begue, Gauthier Beuque, Orianne Weizman, Paul Lucain, Nabil Bouali, Thierry Garban, Marc Villaceque, Jérémie Barraud, Cyril Ferdynus, Louis-Marie Desroche","doi":"10.1016/j.acvd.2025.06.078","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence has emerged as a promising tool to optimize patient care in the field of cardiovascular medicine. However, data on its adoption and utilization by healthcare professionals are scarce.</p><p><strong>Aim: </strong>To explore the factors that support or hinder the adoption of artificial intelligence in cardiology in France.</p><p><strong>Methods: </strong>The INSIGHT-AI France study is a two-wave longitudinal panel survey recontacting the same individuals after 12 months, targeting professionals involved in the management of patients with cardiovascular diseases, including senior cardiologists, residents, nurses, technicians, engineers and decision-makers involved in artificial intelligence development. Participants from academic, public non-academic and private hospitals were recruited using a stratified sampling approach to capture diverse perspectives. Data were collected via SKEZIA, a platform compliant with the General Data Protection Regulation, with secure authentication and longitudinal tracking capabilities. The baseline survey, distributed from December 2024 to March 2025, assessed knowledge, attitudes, beliefs and practices related to artificial intelligence in cardiology. A follow-up survey will be conducted 12 months later to evaluate changes over time. The survey was developed by a scientific committee, with feedback from artificial intelligence and cardiology experts, and was pilot-tested for feasibility. Statistical analyses will include mixed-effects models and regression analyses.</p><p><strong>Conclusions: </strong>This is the first study designed to explore the acceptance and limitation of artificial intelligence use in cardiovascular medicine in France. By identifying key facilitators and barriers, this study aims to inform strategic initiatives for more effective and equitable artificial intelligence implementation in French-speaking healthcare systems.</p>","PeriodicalId":55472,"journal":{"name":"Archives of Cardiovascular Diseases","volume":" ","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unveiling facilitators and barriers to artificial intelligence implementation in cardiac healthcare: Rationale and design of the INSIGHT-AI France study, from the Artificial Intelligence Working Group and the National College of Cardiologists in Training of the French Society of Cardiology.\",\"authors\":\"Antonin Trimaille, Stéphane Lafitte, Floran Begue, Gauthier Beuque, Orianne Weizman, Paul Lucain, Nabil Bouali, Thierry Garban, Marc Villaceque, Jérémie Barraud, Cyril Ferdynus, Louis-Marie Desroche\",\"doi\":\"10.1016/j.acvd.2025.06.078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Artificial intelligence has emerged as a promising tool to optimize patient care in the field of cardiovascular medicine. However, data on its adoption and utilization by healthcare professionals are scarce.</p><p><strong>Aim: </strong>To explore the factors that support or hinder the adoption of artificial intelligence in cardiology in France.</p><p><strong>Methods: </strong>The INSIGHT-AI France study is a two-wave longitudinal panel survey recontacting the same individuals after 12 months, targeting professionals involved in the management of patients with cardiovascular diseases, including senior cardiologists, residents, nurses, technicians, engineers and decision-makers involved in artificial intelligence development. Participants from academic, public non-academic and private hospitals were recruited using a stratified sampling approach to capture diverse perspectives. Data were collected via SKEZIA, a platform compliant with the General Data Protection Regulation, with secure authentication and longitudinal tracking capabilities. The baseline survey, distributed from December 2024 to March 2025, assessed knowledge, attitudes, beliefs and practices related to artificial intelligence in cardiology. A follow-up survey will be conducted 12 months later to evaluate changes over time. The survey was developed by a scientific committee, with feedback from artificial intelligence and cardiology experts, and was pilot-tested for feasibility. Statistical analyses will include mixed-effects models and regression analyses.</p><p><strong>Conclusions: </strong>This is the first study designed to explore the acceptance and limitation of artificial intelligence use in cardiovascular medicine in France. By identifying key facilitators and barriers, this study aims to inform strategic initiatives for more effective and equitable artificial intelligence implementation in French-speaking healthcare systems.</p>\",\"PeriodicalId\":55472,\"journal\":{\"name\":\"Archives of Cardiovascular Diseases\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Cardiovascular Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.acvd.2025.06.078\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Cardiovascular Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.acvd.2025.06.078","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Unveiling facilitators and barriers to artificial intelligence implementation in cardiac healthcare: Rationale and design of the INSIGHT-AI France study, from the Artificial Intelligence Working Group and the National College of Cardiologists in Training of the French Society of Cardiology.
Background: Artificial intelligence has emerged as a promising tool to optimize patient care in the field of cardiovascular medicine. However, data on its adoption and utilization by healthcare professionals are scarce.
Aim: To explore the factors that support or hinder the adoption of artificial intelligence in cardiology in France.
Methods: The INSIGHT-AI France study is a two-wave longitudinal panel survey recontacting the same individuals after 12 months, targeting professionals involved in the management of patients with cardiovascular diseases, including senior cardiologists, residents, nurses, technicians, engineers and decision-makers involved in artificial intelligence development. Participants from academic, public non-academic and private hospitals were recruited using a stratified sampling approach to capture diverse perspectives. Data were collected via SKEZIA, a platform compliant with the General Data Protection Regulation, with secure authentication and longitudinal tracking capabilities. The baseline survey, distributed from December 2024 to March 2025, assessed knowledge, attitudes, beliefs and practices related to artificial intelligence in cardiology. A follow-up survey will be conducted 12 months later to evaluate changes over time. The survey was developed by a scientific committee, with feedback from artificial intelligence and cardiology experts, and was pilot-tested for feasibility. Statistical analyses will include mixed-effects models and regression analyses.
Conclusions: This is the first study designed to explore the acceptance and limitation of artificial intelligence use in cardiovascular medicine in France. By identifying key facilitators and barriers, this study aims to inform strategic initiatives for more effective and equitable artificial intelligence implementation in French-speaking healthcare systems.
期刊介绍：
The Journal publishes original peer-reviewed clinical and research articles, epidemiological studies, new methodological clinical approaches, review articles and editorials. Topics covered include coronary artery and valve diseases, interventional and pediatric cardiology, cardiovascular surgery, cardiomyopathy and heart failure, arrhythmias and stimulation, cardiovascular imaging, vascular medicine and hypertension, epidemiology and risk factors, and large multicenter studies. Archives of Cardiovascular Diseases also publishes abstracts of papers presented at the annual sessions of the Journées Européennes de la Société Française de Cardiologie and the guidelines edited by the French Society of Cardiology.
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