Generative artificial intelligence in cardiovascular specialty care: a scoping review

Area of Science:

• Cardiovascular Nursing
• Artificial Intelligence
• Health Informatics

Background:

• Generative artificial intelligence (AI) research is expanding, but applications in specialized nursing fields, particularly cardiovascular nursing, remain underexplored.
• Existing studies primarily focus on general nursing scenarios, lacking a systematic overview of AI in cardiovascular specialty nursing.

Purpose of the Study:

• To review existing literature on the application of generative artificial intelligence in specialized cardiovascular nursing.
• To inform future research and practice by synthesizing current findings and identifying gaps.

Main Methods:

• A comprehensive scoping review adhering to JBI guidelines and PRISMA-ScR.
• Searched multiple databases (PubMed, Embase, Web of Science, etc.) for English and Chinese studies up to March 29, 2025.
• Rigorous screening of titles, abstracts, and full texts by two independent evaluators.

Main Results:

• Nineteen studies were included, utilizing text generation models, multimodal models, temporal prediction models, and chatbots.
• Key applications include clinical decision support, patient health management, and nursing education/counseling.
• AI demonstrated effectiveness in reducing workload and enabling precise interventions, but faced challenges in health education (e.g., logical gaps, poor quality, lack of humanistic care).

Conclusions:

• Generative AI offers significant technical support for intelligent transformation in cardiovascular specialty care, particularly in decision support and patient management.
• Addressing current limitations in AI applications is crucial for deeper integration into cardiovascular nursing.
• Future research should prioritize the development of specialized multimodal AI models for this field.