AI-Driven Translational Innovations in Cardiovascular Health: Predictive Models and Ethical Horizons

This article collection focuses on the rapidly emerging utilization of artificial intelligence (AI) to revolutionize cardiovascular disease prediction and management. With the successful implementation of models like PowerAI-CVD, which integrates AI with clinical data to predict major adverse cardiovascular events, the potential for AI-driven tools in clinical settings is immense. Manuscripts in this Research Topic will explore expanding AI applications in cardiovascular medicine, including real-time risk assessment, personalized treatment plans, and integration with wearable technology for continuous monitoring.We aim to address the challenges and ethical considerations of AI in healthcare, ultimately contributing to the enhancement of patient outcomes through technological innovation. This Research Topic highlights novel advances in translating innovative AI tools and methods into clinical practice, particularly related to cardiovascular medicine. Articles that examine basic and translational research are welcomed, as well as articles describing theoretical and ethical issues. We encourage both original research and review articles.Articles can include, but are not limited to, the following topics:• The future potential of AI as it relates to cardiovascular medicine;• Innovative, translational approaches to advance AI in healthcare and cardiovascular medicine;• Theories related to the impact of AI on medical practice;• Obstacles to be overcome to use AI effectively in diagnosis and treatment of CVDs;• Large language models for biomarker discovery;• Potential or new tools being developed for AI-powered drug discovery related to CVDs;• Potential or new tools being developed using AI to prevent adverse outcomes from therapies ranging from surgery to drug therapy;• Agentic AI systems accelerating translational cardiovascular research and discovery;• Explainable AI methods to support understanding, transparency, and trust in AI-guided precision medicine;• Managing perception of AI with patients and how this affects clinical outcomes;• Translational advances in tools and methods of AI applied to CVDs;• Translational science approaches that cross boundaries between disciplines to promote AI innovation;• Benefits and challenges associated with AI approaches to interpreting basic and clinical big data from omics or other sources;• Challenges associated with AI interpretation of findings derived from training models on vast amounts of unlabeled data or data of poor quality. Topic editors: DeLisa Fairweather, Raquel Dias, Cui Tao Source: https://www.frontiersin.org/research-topics/76041/ai-driven-translational-innovations-in-cardiovascular-health-predictive-models-and-ethical-horizons