Call for Papers: Generative and Multimodal AI in Digital Cardiovascular Medicine.
JMIR Publications is pleased to announce a new section in JMIR Cardio titled “Generative and Multimodal AI in Digital Cardiovascular Medicine.” This section will publish peer-reviewed, time-sensitive research on innovations, challenges, and open questions at the intersection of AI and cardiology.
In 2023, JMIR Cardio published a call for papers exploring the potential of generative AI in cardiovascular medicine and its subspecialties. Since then, the field has moved quickly from demonstration to deployment, and the evidence base has not always kept pace.
Cardiovascular diseases remain the leading cause of mortality across the world [1]. Generative and multimodal AI may improve diagnostic accuracy, clinical efficiency, access to expertise, and patient care. However, demonstrating technical performance alone is insufficient to establish clinical value. Responsible implementation requires rigorous validation, appropriate governance, and evaluation across diverse populations, health care systems, and real-world settings.
Claims of benefit and evidence of benefit are not the same thing.
Beyond technical and algorithmic performance, this section will prioritize research that evaluates the clinical value of AI in cardiovascular medicine. This includes evidence of effectiveness in real-world care, generalizability across populations and health care settings, impact on access and equity, feasibility of implementation and scaling, and costs.
We particularly welcome:
- Original research evaluating generative and multimodal AI against current standards of care: prospective, pragmatic, implementation, and real-world studies
- Studies reporting negative, null, or mixed results
- Viewpoints presenting a well-argued, evidence-based case against particular generative AI applications in cardiovascular medicine
Topics of Interest:
Submissions are invited on, but not limited to, the following topics:
- Clinical diagnosis, risk prediction, and decision support: Generative AI, multimodal models, and large language models applied to cardiovascular diagnosis, risk stratification, treatment selection, clinical decision support, and personalized care planning
- Multimodal cardiovascular data integration: Integration of imaging, ECG and electrophysiological data, electronic health records, laboratory data, patient-generated data, and mobile or wearable sensor streams, with particular interest in clinically validated multimodal approaches
- Implementation and real-world cardiovascular care: Prospective evaluation, workflow integration, clinician-AI interaction, scalability, postdeployment performance, resource utilization, and the effectiveness and cost-effectiveness of AI-enabled cardiovascular care
- Patient-centered care and access: Conversational agents, natural language generation, and LLM-driven tools to enhance patient engagement, prevention, cardiac rehabilitation, remote care, and care pathway workflows, including studies examining whether AI improves or inadvertently restricts access to cardiovascular expertise and services
- Equity, sex, and gender considerations: Development and validation across diverse populations and health care settings; algorithm bias and digital exclusion; and sex- and gender-specific cardiovascular conditions, including maternal and perinatal cardiovascular health
- Evidence standards and responsible AI: Research defining and evaluating the evidence required for clinical adoption of cardiovascular AI, including external validation, safety and failure analysis, human oversight, generalizability, postdeployment monitoring, data governance, and privacy and regulatory evaluation
How to Submit:
Submit an article by selecting “Generative and Multimodal AI in Digital Cardiovascular Medicine” in the “Section” drop-down list. See the article How do I submit to a theme issue? in our Knowledge Base and consult our Instructions for Authors for more information.
All submissions will undergo a rigorous peer-review process, and accepted articles will be published under the theme "Generative and Multimodal AI in Digital Cardiovascular Medicine.”
All peer-reviewed articles will be made immediately and permanently open access.
Articles will be made immediately available in JMIR Preprints (with a DOI), if authors select this option at submission.